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Posts Tagged ‘national cancer institute’

Reporter: Aviva Lev-Ari, PhD, RN

CT Scanner Delivers Less Radiation

Faster, more sensitive scans and better image processing may reduce the risk of x-ray-related cancers.

 WHY IT MATTERS

A new CT scanner exposes patients to less radiation while providing doctors with clearer images to help with diagnoses, according to researchers at the National Institutes of Health.

“CT” stands for Computerized Tomography, which involves combining lots of x-ray images taken from different angles into a three-dimensional view of what’s inside the body. The technology can be especially useful for diagnoses in emergency situations, and the number of CT scans in recent years has increased dramatically, says Marcus Chen, a cardiovascular imager at the National Heart, Lung and Blood Institute, in Bethesda, Maryland.  But the increase in the use of CT scans raises concerns about the amount of radiation to which patients are exposed, says Chen.

The risk of developing cancer from the radiation delivered by one CT scan is low, but the large number of scans performed each year—more than 70 million—translates to a significant risk. Researchers at the National Cancer Institute estimated that the 72 million CT scans performed in the U.S. in 2007 could lead to 29,000 new cancers. On average, the organ studied in a CT scan of an adult receives around 15 millisieverts of radiation, compared with roughly 3.1 millisieverts of radiation exposurefrom natural sources each year.

This concern has led researchers to seek ways to reduce the amount of radiation exposure a patient receives in a scan. They are working to improve both hardware, to make the scans go faster and need less repetition, and software, to process the x-ray data better (see “Clear CT Scans with Less Radiation”).

The new CT scanning system, from Toshiba Medical, combines several improvements to reduce radiation exposure. The overall body of a CT scanner is shaped like a large ring. An x-ray tube and a detector spin separately in the ring, opposite one another, and a patient lies in the center.  X-rays travel through the patient as they are delivered by the tube and captured by the detectors. The new Toshiba machine has five times as many detectors as most machines, which means that more of an organ can be captured at a time, decreasing the number of passes of the scanner required.

The x-ray components in the new system also spin faster—it takes only 275 milliseconds for them to complete a rotation, instead of 350 millisesconds—which means a patient gets irradiated for less time. In cases where doctors are looking at a moving organ such as the heart, the faster spinning also reduces the number of times a doctor may need to try to get a good image. “It’s like having faster film in your camera,” says Chen.  Changes to the way the system generates x-rays and computes the images also mean patients spend less time getting hit with radiation.

Chen and colleagues at the National Heart Lung and Blood Institute used the Toshiba system to examine 107 adult patients of different ages and sizes for plaque buildup and cardiovascular problems. Patient size matters because more x-rays are required to image a larger person. “A lot of imaging centers will use one setting for all patients,” says Chen. “You get beautiful image quality on everybody, but the downside is that some patients get more radiation than they probably should.” In his study, the system takes a quick preliminary scan that uses low-dose x-rays to figure out how big a patient is and how much radiation will be needed for the diagnostic image.

Most patients who got a scan in the new Toshiba machine received 0.93 millisieverts of radiation, and almost every patient received less than 4 millisieverts. Radiation exposure was decreased by as much as 95 percent relative to other CT scanners currently in use.

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The reader is advised to review Alternative #3 in the following article, published on 3/10/2013, including the Editorial in NEJM by Dr. Redberg, UCSF, included in the article, prior to reading the content, below — as background on this important topic having the potential to change best practice and standard of care in the ER/ED.

Acute Chest Pain/ER Admission: Three Emerging Alternatives to Angiography and PCI – Corus CAD, hs cTn, CCTA

CCTA for Chest Pain Cuts Costs, Admissions

By Eric Barnes, AuntMinnie.com staff writer

May 14, 2013 — One of the largest studies yet comparing medical resource use and outcomes among chest pain patients found that coronary CT angiography (CCTA) reduced medical resource utilization compared to standard care, generating fewer hospital admissions and shorter emergency room stays, researchers reported in the Journal of the American College of Cardiology.

The retrospective study compared matched cohorts of nearly 1,000 patients presenting with chest pain before and after implementation of routine CCTA evaluation. The study team from Stony Brook, NY, and two other institutions found that patients receiving the standard workup for chest pain — which is to say, mostly observation — were admitted to the hospital almost five times as frequently as patients receiving CT. The standard workup patients also had significantly longer stays when admitted.

The rates of invasive angiography without revascularization and recidivism were also much higher for patients receiving standard care (JACC, May 14, 2013).

“I think the take-home message is that CT done correctly by experts with the resources to do it correctly on a routine basis is not only safe and feasible, but reduces healthcare resource utilization,” said lead author Dr. Michael Poon, from Stony Brook Medical Center, in an interview with AuntMinnie.com.

More than $10 billion in costs

Caring for chest pain is an expensive proposition in the U.S., costing upward of $10 billion a year for some 6 million emergency department (ED) visits. To reduce the problem of overcrowded emergency rooms, some hospitals have implemented chest pain evaluation units, but the care isn’t comprehensive or necessarily all that helpful, Poon said.

“It has been a problem and a major dilemma for emergency rooms because for most patients, it’s a false alarm,” he said. “I would say nine out of 10 are false alarms, but how to pick out that one is very tricky and costly. So what most hospitals tend to do is a one-size-fits-all policy where everybody gets blood tests and an electrocardiogram, and they keep patients in the ED for an extended period of time. So if you come in Friday, you may stay until Monday.”

Coronary CTA has been shown to be safe and cost-effective for acute chest pain evaluation in several smaller studies and in three smaller multicenter trials, but those studies have been limited by a lack of CT availability outside of weekdays and office hours, while EDs must operate 24/7, Poon said.

“All of those studies were done in a randomized, controlled fashion and in an artificial environment,” where each patient was randomized to either a stress test or CT during weekday office hours, Poon said. “But in real life, there is no such thing; it cannot be done.”

More often, chest pain patients get a couple of tests and several hours of observation before they are sent home.

Poon and colleagues from Stony Brook, William Beaumont Hospital, and the University of Toronto wanted to do a “real-world” observational study to show that CT remained cost-effective and efficient for triaging chest pain patients.

The study sought to compare the overall impact of CT on clinical outcomes and efficacy, when comparing CCTA and the hospital’s standard evaluation for the triage of chest pain patients, with CCTA available 12 hours a day, seven days a week.

From a total of 9,308 patients with a chest pain diagnosis upon admission, the study used a matched sample of 894 patients without a history of coronary artery disease and without positive troponin or ischemic changes on an electrocardiogram.

Patients undergoing CT were scanned on a 64-detector-row scanner (LightSpeed VCT, GE Healthcare) following administration of iodinated contrast and metoprolol as a beta-blocker for those with heart rates faster than 65 beats per minute (bpm).

Those with a body mass index (BMI) less than 30 were scanned at 100 kV, while those with a BMI between 30 and 50 were scanned at 120 kV. Retrospective gating was reserved for patients whose heart rates remained above 65 bpm. Obstructive stenosis was defined as 50% or greater lumen narrowing.

CT choice faster, more efficient

The results showed a lower overall admission rate of 14% for CCTA, compared with 40% for the standard of care (p < 0.001). In fact, patients undergoing standard evaluation were 5.5 times more likely to be admitted (p < 0.001) than CCTA patients.

The length of stay in the ED was 1.6 times longer for standard care (p < 0.001) than for CCTA. For patients undergoing CCTA, the median radiation dose was 5.88 mSv.

“We also showed that the recidivism rate is higher for standard of care, meaning that they come back within one month with recurrent chest pain,” Poon said. The odds of returning to the ED within 30 days were five times greater for patients in the standard evaluation group (odds ratio, 5.06; p = 0.022).

“In the era of Obamacare, this is a penalty to the hospital; you don’t want the patient returning within one month with the same diagnosis,” he said. When that happens, “you’re not only not getting paid, you have to pay a penalty. It’s a double whammy. We also show that downstream invasive coronary angiography is significantly less in the CCTA arm.”

More invasive angiography

Patients receiving standard care were seven times more likely to undergo invasive coronary angiography without revascularization (odds ratio, 7.17; p ≤ 0.001), while neither patient group was significantly more likely to undergo revascularization.

“Many physicians use [catheterization] as a way of getting patients in and out of the hospital,” Poon said. However, the cost is more than $10,000 per procedure.

The high rate of angiography without revascularization in the standard care group was not seen in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) I and II trials, where all patients in the standard care group underwent stress testing before angiography was considered, he said.

Poon credited the ROMICAT trials’ routine use of stress tests with diminishing CT’s relative advantage in resource use. “In the real world, that is not available,” he said. The present study, in which only about 20% of the standard care patients underwent stress tests, is more realistic.

Finally, Poon and colleagues showed no difference in rates of myocardial infarction between CT and the standard of care within the first 30 days of follow up. However, that is changing as patients are followed for longer time periods, he noted.

“We see a trend starting to diverge in our next report, which follows [patients] for six months,” he said. “You see a lot more acute myocardial infarction in the standard care arm, and we’re going to extend it for a year.”

The authors concluded that using CCTA to rule out acute coronary syndromes in low-risk chest pain patients is likely to improve doctors’ ability to triage patients with the common presentation of chest pain. The result of this approach appears to be fewer hospital admissions, shorter stays, less recidivism, less invasive angiography, and better patient outcomes.

In any case, Poon said, the study method is permanent at Stony Brook University, where the standard of care now incorporates CCTA.

“We didn’t stop doing it after the study,” he said. “If you look at some of the randomized, controlled studies, they actually went back to the standard of care.” They had to because those kinds of protocols are only practical with a grant.

Related Reading

CORE 320 study evaluates CCTA and SPECT for CAD diagnosis, March 25, 2013

Study affirms CCTA’s value to rule out myocardial infarction, March 19, 2013

CCTA predicts heart attack in people without risk factors, February 19, 2013

Study: Use CCTA 1st for lower-risk chest pain patients, February 4, 2013

2010 CCTA appropriateness criteria yield mixed results, January 31, 2013
Copyright © 2013 AuntMinnie.com

http://www.auntminnie.com/index.aspx?sec=sup&sub=cto&pag=dis&ItemID=103419&wf=5447

Other related articles on this Open Access Online Scientific Journal include the following:

Economic Toll of Heart Failure in the US: Forecasting the Impact of Heart Failure in the United States – A Policy Statement From the American Heart Association

Aviva Lev-Ari, PhD, RN, 4/25/2013

http://pharmaceuticalintelligence.com/2013/04/25/economic-toll-of-heart-failure-in-the-us-forecasting-the-impact-of-heart-failure-in-the-united-states-a-policy-statement-from-the-american-heart-association/

Diagnosis of Cardiovascular Disease, Treatment and Prevention: Current & Predicted Cost of Care and the Promise of Individualized Medicine Using Clinical Decision Support Systems

Larry H Bernstein, MD, FACP and Aviva Lev-Ari, PhD, RN, Curator, 5/15/2013

http://pharmaceuticalintelligence.com/2013/05/15/diagnosis-of-cardiovascular-disease-treatment-and-prevention-current-predicted-cost-of-care-and-the-promise-of-individualized-medicine-using-clinical-decision-support-systems-2/

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Ultrasound-based Screening for Ovarian Cancer

Author: Dror Nir, PhD

Occasionally, I check for news on ovarian cancer screening. I do that for sentimental reasons; I started the HistoScanning project aiming to develop an effective ultrasound-based screening solution for this cancer.

As awareness for ovarian cancer is highest in the USA, I checked for the latest news on the NCI web-site. I found that to-date: “There is no standard or routine screening test for ovarian cancer. Screening for ovarian cancer has not been proven to decrease the death rate from the disease.

Screening for ovarian cancer is under study and there are screening clinical trials taking place in many parts of the country. Information about ongoing clinical trials is available from the NCI Web site.”

I also found that:

Estimated new cases and deaths from ovarian cancer in the United States in 2013:

  • New cases: 22,240
  • Deaths: 14,030

To get an idea on the significance of these numbers, lets compare them to the numbers related to breast cancer:

Estimated new cases and deaths from breast cancer in the United States in 2013:

  • New cases: 232,340 (female); 2,240 (male)
  • Deaths: 39,620 (female); 410 (male)

Death rate of ovarian cancer patients is almost 4 times higher than the rate in breast cancer patients!

Therefore, I decided to raise awareness to the results achieved for ovarian HistoScanning in a double-blind multicenter European study that was published in European Radiology three years ago. The gynecologists who recruited patients to this study used standard ultrasound machines of GE-Medical. I would like as well to disclose that I am one of the authors of this paper:

A new computer-aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: results of a multicentre validation study, Olivier Lucidarme et.al., European Radiology, August 2010, Volume 20, Issue 8, pp 1822-1830

Abstract

Objectives

To prospectively assess an innovative computer-aided diagnostic technology that quantifies characteristic features of backscattered ultrasound and theoretically allows transvaginal sonography (TVS) to discriminate benign from malignant adnexal masses.

Methods

Women (n = 264) scheduled for surgical removal of at least one ovary in five centres were included. Preoperative three-dimensional (3D)-TVS was performed and the voxel data were analysed by the new technology. The findings at 3D-TVS, serum CA125 levels and the TVS-based diagnosis were compared with histology. Cancer was deemed present when invasive or borderline cancerous processes were observed histologically.

Results

Among 375 removed ovaries, 141 cancers (83 adenocarcinomas, 24 borderline, 16 cases of carcinomatosis, nine of metastases and nine others) and 234 non-cancerous ovaries (107 normal, 127 benign tumours) were histologically diagnosed. The new computer-aided technology correctly identified 138/141 malignant lesions and 206/234 non-malignant tissues (98% sensitivity, 88% specificity). There were no false-negative results among the 47 FIGO stage I/II ovarian lesions. Standard TVS and CA125 had sensitivities/specificities of 94%/66% and 89%/75%, respectively. Combining standard TVS and the new technology in parallel significantly improved TVS specificity from 66% to 92% (p < 0.0001).

table 3

table 4

An example of an ovary considered to be normal with TVS.

An example of an ovary considered to be normal with TVS.

The same TVS false-negative ovary with OVHS-detected foci of malignancy. The presence of an adenocarcinoma was confirmed histologically.

The same TVS
false-negative ovary with OVHS-detected foci of malignancy. The presence of an
adenocarcinoma was confirmed histologically.

Conclusions

Computer-aided quantification of backscattered ultrasound is  highly sensitive for the diagnosis of malignant ovarian masses.

 Personal note:

Based on this study a promising offer for ultrasound-based screening method for ovarian cancer was published in:  Int J Gynecol Cancer. 2011 Jan;21(1):35-43. doi: 10.1097/IGC.0b013e3182000528.: Mathematical models to discriminate between benign and malignant adnexal masses: potential diagnostic improvement using ovarian HistoScanning. Vaes EManchanda RNir RNir DBleiberg HAutier PMenon URobert A.

Regrettably, the results of these studies were never transformed into routine clinical products due to financial reasons.

Other research papers related to the management of Prostate cancer were published on this Scientific Web site:

Beta-Blockers help in better survival in ovarian cancer

Ovarian Cancer and fluorescence-guided surgery: A report

Role of Primary Cilia in Ovarian Cancer

Squeezing Ovarian Cancer Cells to Predict Metastatic Potential: Cell Stiffness as Possible Biomarker

BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

Warning signs may lead to better early detection of ovarian cancer

 

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Reporter: Aviva Lev-Ari, PhD, RN

 

Track 5

Next-Gen Sequencing Informatics

NGS, Genome-Scale Screening, and HTP Proteomics

Track 5 is dedicated to advances in analysis and intepretation of next-gen data. Topics to be covered include analysis of

sequence variants related to cancer research from NGS data, instruments facilitate a cloud approach for NGS, analysis tools

and workflows, and network biology/network medicine.

TUESDAY, APRIL 9

7:00 am Workshop Registration and Morning Coffee

8:00 Pre-Conference Workshops*

*Separate Registration Required

2:00 – 7:00 pm Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge

Healthtech Institute

4:05 Keynote Introduction

Kevin Brode, Senior Director, Health & Life Sciences, Americas Hitachi

Data Systems

»»4:15 PLENARY KEYNOTE

Do Network Pharmacologists Need Robot Chemists?

Andrew L. Hopkins, DPhil, FRSC, FSB, Division of Biological Chemistry

and Drug Design, College of Life Sciences, University of Dundee

5:00 Welcome Reception in the Exhibit Hall with Poster Viewing

Drop off a business card at the CHI Sales booth for a chance to win 1 of 2

iPads® or 1 of 2 Kindle Fires®!*

*Apple ® and Amazon are not sponsors or participants in this program

WEDNESDAY, APRIL 10

7:00 am Registration and Morning Coffee

8:00 Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:05 Keynote Introduction

Sanjay Joshi, CTO, Life Sciences, EMC Isilon

»»8:15 PLENARY KEYNOTE

Atul Butte, M.D., Ph.D., Division Chief and Associate Professor,

Stanford University School of Medicine; Director, Center for Pediatric

Bioinformatics, Lucile Packard Children’s Hospital; Co-founder,

Personalis and Numedii

8:55 Benjamin Franklin Award & Laureate Presentation

9:15 Best Practices Award Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

Best Practices for Genomic Data Interpretation & Analysis

10:50 Chairperson’s Remarks

Steve Dickman, Founder & CEO, CBT Advisors, Inc.

11:00 CLARITY Challenge

Shamil Sunyaev, Ph.D., Associate Professor, Division of Genetics,

Department of Medicine, Brigham and Women’s Hospital/Harvard

Medical School

11:30 HLA and KIR Typing from NGS Reads with

Omixon Target

Attila Berces, Ph.D., CEO, Omixon

HLA is the most polymorphic region of the human genome

with several segmental duplications and its analysis is a computational

challenge. In this presentation I will show examples including validation

studies of HLA typing from various sources of genomic data: whole genome,

whole exome, targeted amplicon sequencing with Illumina, Ion Torrent and

Roche sequencer.

11:45 Comparison of Genome Analysis Tools

Jason Wang, Co-founder & CTO, Arpeggi, Inc.

A major impediment to clinical sequencing is the paucity of

analysis standards and comparison metrics. We present our

progress towards developing analysis standards, as well an open-access

collaborative tool that enables anyone to define comparison metrics and

compare tool performance. We hope that in making available this resource

we can help fuel a community-driven solution for standardizing genome

analysis pipelines.

12:00 Case Study: Sequencing Informatics System to Profile Genetic

Changes in Tumors

Long Phi Le, M.D., Ph.D., Department of Pathology, Massachusetts

General Hospital

This presentation will discuss the development of a sequencing informatics

system to profile genetic changes in tumors that is in collaboration between

PerkinElmer with Massachusetts General Hospital. This system, based on

PerkinElmer’s Geospiza platforms, will allow genotype analysis to define

key targets.

12:30 Ion Torrent Informatics Enables

Semiconductor Sequencing

Darryl León , Ph.D., Associate Director, Product

Management, Ion Torrent, Life Technologies

Data generated by the Ion Torrent Personal Genome Machine Sequencer or

the Ion Torrent Proton Sequencer are analyzed by Torrent Suite Software.

An overview of the data analysis steps will be provided. Torrent Suite offers

a flexible plug-in system allowing software developers the ability to deliver

custom analysis solutions using the compute resources associated with the

local Torrent Server. For researchers with need for either rich annotations

or controlled data analysis, the Ion Reporter Software offers a streamlined

data analysis and decision engine for use with amplicons, exomes,

or genomes.

1:40 Chairperson’s Remarks

Jeffrey Rosenfeld, Ph.D., IST/High Performance & Research Computing,

University of Medicine & Dentistry of New Jersey (UMDNJ)

Sponsored by

Sponsored by

Sponsored by

Bio-ITWorldExpo.com 18

1:45 Data Intensive Academic Grid (DIAG): A Free Computational Cloud

Infrastructure Designed for Bioinformatics Analysis

Anup Mahurkar, Executive Director, Software Engineering and IT, Institute

for Genome Sciences, University of Maryland School of Medicine

We have deployed the NSF funded Data Intensive Academic Grid (DIAG),

a free computational cloud designed to meet the analytical needs of

the bioinformatics community. DIAG has 200+ registered users from 130

institutions worldwide who conduct large-scale genomics, transcriptomics,

and metagenomics data analysis. Learn about the grid’s architecture, how

to access this free resource, and success stories.

2:15 Performance Comparison of Variant Detection Tools for Next

Generation Sequencing (NGS) Data: An Assessment Using a Pedigree-

Based NGS Dataset and SNP Array

Ming Yi, Ph.D. IT Manager, Functional Genomic Group, Advanced

Biomedical Computing Center, SAIC-Frederick at Frederick National

Laboratory for Cancer Research (formerly National Cancer Institute)

There is an urgent need for the NGS community to be able to make the

right choice out of a large collection of available SNP detection tools. Our

methodology offers a great example of comparing SNP discovery tools and

paving a way to expand such methods in more global scope for comparison.

2:45 Informatics in the Cloud

Karan Bhatia, Ph.D., Solutions Architect, Amazon

Web Services

Learn about how to easily create sophisticated, scalable,

secure pipelines to accelerate life science research with Amazon Web

Services. In this presentation, you will learn how to drive scale out, tightly

coupled and Hadoop based workflows on Amazon EC2, a utility computing

platform that provides a perfect fit for data management and collaboration.

3:15 Refreshment Break in the Exhibit Hall with Poster Viewing

Gene Mapping & Expression

3:45 InSilico DB Genomic Datasets Hub: An Efficient Starting Point for

Managing and Analyzing Genomewide Studies in GenePattern, Integrative

Genomics Viewer, and R/Bioconductor

David Weiss, Ph.D., CEO, InSilico Genomics

Alain Coletta, Ph.D., Co-Founder and CTO, InSilico Genomics

The InSilico DB platform is a powerful collaborative environment, with

advanced capabilities for biocuration, datasets subsetting and combination,

and datasets sharing. InSIlico DB solution architecture will be presented

along with a live demo of the InSilico DB online platform. Learn how more

than 1000 users from top academic and research institutions are using

InSilico DB in their daily research.

4:15 Constructing a Comprehensive Map for Molecules Implicated in

Obesity and Its Induced Disorders

Kamal Rawal, Ph.D., Faculty, Biotechnology and Bioinformatics, Jaypee

Institute of Information Technology

We have constructed a comprehensive map of all the molecules (genes,

proteins, and metabolites) reported to be implicated in obesity. This map

paves the way to understanding the pathophysiology of obesity and identify

drug targets and off-targets for existing drugs. This talk discusses the

integrated approach we used in combining public resources, abstracts, and

research articles to construct this map.

4:45 Quality Assurance: An Essential Step for Gene

Expression Analysis Using Deep Sequencing

Dan Kearns, Director, Software Development, Maverix

Biomics, Inc.

Dave Mandelkern, CEO & Co-Founder, Maverix Biomics, Inc.

With the advancement of deep sequencing technologies, researchers

expect to obtain high quality results from their studies. However, this cannot

be obtained solely by successful sequencing runs. Multiple data checks

and pre-processing must be performed before downstream analysis. In this

case study, we will present an automated quality assurance pipeline that

helps improve gene expression analysis results.

5:00 DDN LS Appliance – Simple Platform for NGS

Analysis, Data Distribution and Collaboration

Jose L. Alvarez, WW Director Life Sciences,

DataDirect Networks

With this unique approach the DDN LS appliance can deliver flexible data

ingest options, optimized data analysis resources, a policy based data

tiering/archive solution and a geo-distributed secure collaboration platform.

The appliance delivers 1.46X better performance on popular LS applications

like Bowtie when compared to NFS based solutions.

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes

THURSDAY, APRIL 11

7:00 am Breakfast Presentation (Sponsorship Opportunity Available) or

Morning Coffee

Gene Mapping & Expression

8:45 Chairperson’s Opening Remarks

8:50 Network Biology and Personalized Medicine in Multiple Sclerosis

Mark Chance, Ph.D., Vice Dean for Research, Proteomics, Case Western

Reserve University

Almost nothing is known about biological factors underlying the remarkable

disease heterogeneity observed across multiple sclerosis (MS) patients,

and there are no accurate biological predictors of disease severity that

can be used for guiding clinical treatment options. Learn about the network

biology methods we are using to analyze blood cell gene expression and

understand good and poor responders to therapy.

9:20 GeneSeer: A Flexible, Easy-to-Use Tool to Aid Drug Discovery by

Exploring Evolutionary Relationships between Genes across Genomes

Philip Cheung, Bioinformatics Group Leader, Scientific Computing,

Dart Neuroscience

GeneSeer is a publicly available tool that leverages public sequence data,

gene metadata information, and other publicly available data to calculate

and display orthologous and paralogous gene relationships for all genes

from several species, including yeasts, insects, worms, vertebrates,

mammals, and primates such as human. This talk describes GeneSeer’s

underlying methods and the user-friendly interface.

9:50 Sponsored Presentations (Opportunities Available)

10:20 Coffee Break in the Exhibit Hall and Poster Competition

Winners Announced

10:45 Plenary Keynote Panel Chairperson’s Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:50 Plenary Keynote Panel Introduction

Yury Rozenman, Head of BT for Life Sciences, BT Global Services

Niven R. Narain, President & CTO, Berg Pharma

»»Plenary Keynote Panel

11:05 The Life Sciences CIO Panel

Panelists:

Remy Evard, CIO, Novartis Institutes for BioMedical Research

Martin Leach, Ph.D., Vice President, R&D IT, Biogen Idec

Andrea T. Norris, Director, Center for Information Technology (CIT)

and Chief Information Officer, NIH

Gunaretnam (Guna) Rajagopal, Ph.D., VP & CIO – R&D IT, Research,

Bioinformatics & External Innovation, Janssen Pharmaceuticals

Cris Ross, Chief Information Officer, Mayo Clinic

Matthew Trunnell, CIO, Broad Institute of MIT and Harvard

Sponsored by

Sponsored by

Sponsored by

19 Bio-ITWorldExpo.com

12:15 Luncheon in the Exhibit Hall with Poster Viewing

Panel Session: Building the IT Archetecture of the New York

Genome Center

2:00 Panel Session: Building the IT Architecture of the New York

Genome Center

Moderator: Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

Christopher Dwan, Acting Senior Vice President, IT, New York

Genome Center

Kevin Shianna, Senior Vice President, Sequencing Operations, New York

Genome Center

Sanjay Joshi, CTO, Life Sciences, EMC Isilon Storage Division

Robert B. Darnell, M.D., Ph.D., President & Scientific Director, New York

Genome Center

George Gosselin, CTO, Computer Design & Integration LLC

In 2011, a consortium of 11 major academic and medical organizations in

and around New York announced the creation of the New York Genome

Center (NYGC). Under the direction of Nancy Kelley, the NYGC aspires to

be a world-class genomics and medical research center, and is currently

undergoing construction in the heart of Manhattan. NYGC management

has the opportunity to design and create a state-of-the-art IT and data

management infrastructure to handle, store and share the output from

what will rapidly become one of the world’s foremost genome sequencing

facilities. This series of talks will describe the thinking that went into the

design, creation and construction of the NYGC’s IT infrastructure and entire

data management strategy.

4:00 Conference Adjourns

 

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Larry H Bernstein, MD, FCAP
Pharmaceutical Intelligence

UPDATED 4/23/2020:  New Design for Phase 1 pediatric oncology trials to expedite dose escalation studies.

Clinical Trials Revisited

http://pharmaceuticalintelligence.com/2013/04/03/clinical-trials-revisit/

Cancer Clinical Trials of Tomorrow

Advances in genomics and cancer biology will alter the design of human cancer studies

By Tomasz M. Beer | April 1, 2013   The Scientist
We stand on the cusp of significant change in the fundamental structure of cancer clinical trials, as the emphasis begins to shift from large-scale studies of relatively unselected patients to smaller studies testing more narrowly targeted therapies in molecularly characterized populations.
The previous (and still current) generation of trials established the cancer treatment standards used today. Trials that demonstrated the value of combination chemotherapy in the adjuvant treatment of breast cancer are an excellent example. Meticulous development of treatment regimens through Phase 1 and Phase 2 trials, followed by large-scale comparisons of the new regimens to established treatment protocols, have defined the modern practice of oncology for the last 4 decades. Future cancer clinical trials will be very different from those of the past, adopting a more personalized, sometimes called “precision,” approach.
It is, of course, not entirely true that past clinical trials did not include efforts to target treatments to the right patients. Where possible, targeted therapies are already being implemented. Using the presence of endocrine receptors to guide endocrine therapy for breast cancer was one of the first forays into molecular selection of patients. Unfortunately, the ability to select subgroups of patients for study has been severely curtailed by a still-limited knowledge of human cancer biology.
This is rapidly changing, however, thanks to advances in genomics and comprehensive cancer biology research over the last decade. Large-scale efforts, such as The Cancer Genome Atlas, are comprehensively defining many of the crucial molecular characteristics of human malignancies by illuminating genetic alterations that are clinically and biologically important, and which, by virtue of their functional roles, are viable targets for cancer treatment. At the same time, the ability to design small-molecule inhibitors of specific cancer targets is rapidly accelerating. In 2011, two new agents exemplified the power of these trends: crizotinib was approved for the treatment of lung cancers that harbor a specific mutation in the ALK gene, and vemurafenib was approved for the treatment of melanomas with a specific BRAF mutation. In both cases, the drugs were approved along with companion diagnostic tests that identify patients with the target mutation, who are therefore likely to benefit from treatment.

Smaller, more precise trials ahead

Clinical trials are being transformed by these trends. It will not happen overnight, as the knowledge of cancer biology and the availability of targeted agents are uneven. Unselected populations of patients will still be studied, but it is inevitable that there will be a rise in the number of trials that incorporate molecular tumor testing prior to treatment, with treatment selection informed by the molecular features of each individual’s cancer. Such personalized trials have the potential to yield better outcomes by increasing the probability of response and to employ less toxic therapies by increasingly targeting cancer-specific functions, rather than normal proliferative functions.
To the extent that targeted therapies will prove more effective when given to selected patients, clinical trials should get dramatically smaller. Trial size is largely driven by how effective the treatment is expected to be, so fewer participants are needed when the therapeutic benefit is larger. But the promise of smaller trials will not to be universal; for example, when two targeted agents are compared to one another in the same molecularly selected population, the differences in efficacy may be small and larger trials will be required.
As approaches to cancer treatment advance, there will need to be continual engagement with patients and with cancer survivors.
Furthermore, smaller trials may not necessarily move faster or be easier to complete, as they will require the “right patients,” who may be hard to find. Many of the mutations that represent promising targets are present in a minority of tumors. Today, molecular characterization of tumors is often done as part of the screening process for each trial. Many, and sometimes most, of the patients prove ineligible, making this approach frustrating and difficult to carry out. A better avenue of attack would be to make comprehensive molecular characterization of tumors a routine part of establishing a patient’s eligibility for a range of therapies. With the plummeting cost of genomic analysis, one can envision a day in the near future when a complete cancer genome (and perhaps other molecular evaluations) becomes a standard component of an initial diagnostic evaluation. Patients will be armed with molecular information about their own tumors, and thus able to make more-informed decisions about standard and investigational therapies that match the mutations driving their cancer.

New challenges

The road to personalized and targeted treatment strategies will offer new challenges. For rare targets that are present in a minority of cases across many different types of cancers, one will have to consider clinical trials that include a number of different cancers. There are many design pitfalls to such trials, chiefly the additional clinical and molecular heterogeneity introduced by the inclusion of more than one cancer type. Despite these challenges, it will inevitably make sense in some settings to select patients who share a particular tumor biology, regardless of the tissue of origin.
Another major challenge is how to combine targeted therapies to improve clinical outcomes. To date, targeted therapies have not been able to cure advanced solid tumors. Clinical benefits, while sometimes quite impressive when compared to marginally effective treatments, still fall far short. It stands to reason that redundant survival and growth pathways enable tumors to overcome therapies that inhibit a single target. The simultaneous inhibition of relevant redundant pathways may yield dramatically better results, but will also dramatically increase the complexity of molecularly personalized clinical trials.
As approaches to cancer treatment advance, there will need to be continual engagement with patients and with cancer survivors. Fewer than 5 percent of adult cancer patients participate in a clinical trial. To carry out meaningful clinical trials in the future, that number must increase. This will be most important for treatments that target relatively rare mutations; a large number of potential volunteers will have to be screened to identify a sufficient number who harbor the relevant target. To succeed, we must partner with a much larger fraction of cancer patients.
Designing and executing future cancer clinical trials will not be easy, but physician-scientists are armed with a fast-growing body of omics-informed knowledge with which to surmount these hurdles.
Tomasz M. Beer is deputy director of the Knight Cancer Institute and a professor of medicine at Oregon Health & Science University in Portland. He is the coauthor of Cancer Clinical Trials: A Commonsense Guide to Experimental Cancer Therapies and Clinical Trials. Written for people living with cancer, the book is accompanied by a blog (www.cancer-clinical-trials.com) that seeks to disseminate knowledge about clinical trials.

Tags

tumor suppression, tumor heterogeneity, genetics & genomics, disease/medicine, clinical trials, chemotherapy, cancer genomics and cancer

UPDATED 4/23/2020:  New Design for Phase 1 pediatric oncology trials to expedite dose escalation studies.

 

REVIEW

Ushering in the next generation of precision trials for pediatric cancer

Steven G. DuBois, Laura B. Corson, Kimberly Stegmaier, Katherine A. Janeway

Science  15 Mar 2019:Vol. 363, Issue 6432, pp. 1175-1181 DOI: 10.1126/science.aaw4153

 

Abstract

Cancer treatment decisions are increasingly based on the genomic profile of the patient’s tumor, a strategy called “precision oncology.” Over the past few years, a growing number of clinical trials and case reports have provided evidence that precision oncology is an effective approach for at least some children with cancer. Here, we review key factors influencing pediatric drug development in the era of precision oncology. We describe an emerging regulatory framework that is accelerating the pace of clinical trials in children as well as design challenges that are specific to trials that involve young cancer patients. Last, we discuss new drug development approaches for pediatric cancers whose growth relies on proteins that are difficult to target therapeutically, such as transcription factors.

Some terms from the bibliography:

3+3 design: A commonly used rule-based design for phase 1 clinical trials in which patients are enrolled in cohorts of three patients, and decisions to increase or decrease the dose level for the next three participants are based on toxicities observed in those three patients.

 

Basket trial: A precision oncology trial design in which patients with many different cancer types are enrolled, the tumor is tested for a set of biomarkers of interest, and then patients are assigned to one of several clinical trial subprotocols based on the presence of a biomarker corresponding to a particular molecularly targeted therapy.

 

Bayesian model–based trial designs: A broad class of trial designs that use data known before the trial as well as data obtained during the conduct of the trial to adapt trial parameters as more information becomes available

Continual reassessment method: One example of a Bayesian model–based trial design in which an initial mathematical model of the relationship between drug dose and probability of unacceptable toxicity is continually updated as new information becomes available to assign subsequent patients to a dose anticipated to have an unacceptable toxicity rate below a set rate.

First-in-child trial: The first clinical trial of a specific agent to include a pediatric population, traditionally considered patients <18 years of age.

 

Rolling 6 design: A variation of the 3+3 design in which up to six participants may be enrolled to a dosing cohort before enrollment pauses to assess toxicity.

Safety run-in: An initial component of a phase 2 or phase 3 trial in which a small group of patients are treated with a previously untested regimen to evaluate toxicity before opening the trial to a larger group of participants.

Umbrella trial: A precision oncology trial design in which patients with a specific cancer type are enrolled, tumor is tested for a set of biomarkers of interest, and then patients are assigned to one of several clinical trial subprotocols based on the presence of a biomarker corresponding to a particular molecularly targeted therapy.

 

In this review article, DuBois et al describe new paradigms for pediatric precision oncology trial design and how these designs should be contrasted with the old models and differentiate from the design for these types of trials in the adult.  As the genomic landscape of pediatric tumors is becoming clearer (12) the authors noticed two themes which are becoming evident:

  1. Pediatric cancers harbor certain genomic mutations rarely seen in adult cancers
  2. Pediatric cancers share some genomic alterations and mutational gene signatures with adult tumors

However there is only a small number of pediatric clinical trials to investigate if specific genetic mutations predict outcome to a given personalized therapy.

            Thus, there an urgent need for precision clinical trials in pediatric cancers.

Several reviews have described numerous ongoing and recently completed trials however most are phase 1 dose escalation trials including basket trials and umbrella trials but based on previous data from adult trials using the same precision drug.  For example, pediatric trials involving the TRK inhibitor laratrectinib in tumors harboring a NTRK fusion gene or a pediatric crizotinib trial for pediatric glioblastomas having an ALK fusion protein have shown great success yet most of the early phase 1 work was based on adults or carried out in a way that does not take advantage of the new regulatory framework designed to expedite new drugs for adult precision medicines.

Speeding up the early phase trials in pediatric cancers: new trial design paradigms

Dose escalation phase I trials have, traditionally been the starting point for clinical development of new pediatric anticancer drugs however these first in child trials have seriously lagged their adult counterparts by many years.  These trials relied on the standard 3 x 3  or rolling six trial design, and doses escalated until a pediatric MTD  (maximum tolerated dose) was achieved.  In recent years new precision medicine pediatric trial design has been adopted to expedite the process, based on the fundamental shift in thinking that many new oncology agents will not have a true MTD when tested in adults.

Doses in phase 1 trials for targeted therapies like those in precision medicine are usually escalated based on considerations other than toxicity, like pharmacodynamics or biomarker analysis.  A pediatric phase 1 dose escalation trial may require more subjects than an adult trial.  But

although these newer approaches to early-phase trial design more efficiently establish a pediatric dose, they do little to advance our understanding of with patients are most likely to benefit from a new therapy.

Thus the need for good biomarkers to be included early on in these initial trial designs.  For example, Dana Farber’s first in child clinical trial NCT03654716, a Phase 1 Study of the Dual MDM2/MDMX Inhibitor ALRN-6924 in Pediatric Cancer (as a possible treatment for resistant (refractory) solid tumor, brain tumor, lymphoma or leukemia), are reducing the time children are waiting for entry into a trial, as unselected patients can enroll and the biomarker, increased MDM2 expression is used to determine those patients who go on to phase 2 dose escalation. In other cases, such as NCI Children’s Oncology Group basket trials, they have completely supplanted formal phase 1 trial design and instead incorporated molecularly targeted therapies based on adult doses but adjusted for patient size.  The use of combinations with traditional therapies in trial design is also helping to speed up the process for enrollment.  The authors also suggest that tumor profiling is pertinent however should be put in trial design so the costs to patients can be covered by the trial funds.

 

Figure 1Fig. 1 Evolution of precision trials for pediatric cancer.

Illustration: Kellie Holoski/Science

Source: Ushering in the next generation of precision trials for pediatric cancer BY STEVEN G. DUBOIS, LAURA B. CORSON, KIMBERLY STEGMAIER, KATHERINE A. JANEWAY SCIENCE 15 MAR 2019 : 1175-1181 https://science.sciencemag.org/content/363/6432/1175

 

  1. S. N. Gröbner, B. C. Worst, J. Weischenfeldt, I. Buchhalter, K. Kleinheinz, V. A. Rudneva, P. D. Johann, G. P. Balasubramanian, M. Segura-Wang, S. Brabetz, S. Bender, B. Hutter, D. Sturm, E. Pfaff, D. Hübschmann, G. Zipprich, M. Heinold, J. Eils, C. Lawerenz, S. Erkek, S. Lambo, S. Waszak, C. Blattmann, A. Borkhardt, M. Kuhlen, A. Eggert, S. Fulda, M. Gessler, J. Wegert, R. Kappler, D. Baumhoer, S. Burdach, R. Kirschner-Schwabe, U. Kontny, A. E. Kulozik, D. Lohmann, S. Hettmer, C. Eckert, S. Bielack, M. Nathrath, C. Niemeyer, G. H. Richter, J. Schulte, R. Siebert, F. Westermann, J. J. Molenaar, G. Vassal, H. Witt, B. Burkhardt, C. P. Kratz, O. Witt, C. M. van Tilburg, C. M. Kramm, G. Fleischhack, U. Dirksen, S. Rutkowski, M. Frühwald, K. von Hoff, S. Wolf, T. Klingebiel, E. Koscielniak, P. Landgraf, J. Koster, A. C. Resnick, J. Zhang, Y. Liu, X. Zhou, A. J. Waanders, D. A. Zwijnenburg, P. Raman, B. Brors, U. D. Weber, P. A. Northcott, K. W. Pajtler, M. Kool, R. M. Piro, J. O. Korbel, M. Schlesner, R. Eils, D. T. W. Jones, P. Lichter, L. Chavez, M. Zapatka, S. M. Pfister, ICGC PedBrain-Seq Project, ICGC MMML-Seq Project, The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). 10.1038/nature25480pmid:29489754

 

2.  X. Ma, Y. Liu, Y. Liu, L. B. Alexandrov, M. N. Edmonson, C. Gawad, X. Zhou, Y. Li, M. C. Rusch, J. Easton, R. Huether, V. Gonzalez-Pena, M. R. Wilkinson, L. C. Hermida, S. Davis, E. Sioson, S. Pounds, X. Cao, R. E. Ries, Z. Wang, X. Chen, L. Dong, S. J. Diskin, M. A. Smith, J. M. Guidry Auvil, P. S. Meltzer, C. C. Lau, E. J. Perlman, J. M. Maris, S. Meshinchi, S. P. Hunger, D. S. Gerhard, J. Zhang, Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours. Nature 555, 371–376 (2018). 10.1038/nature25795pmid:29489755

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Curator: Aviva Lev-Ari, PhD, RN

On 3/13/2013 Forbes Science Writer, Metthew Herper, presented a curated article about the protein Cas9. With a compelling title like 

This Protein Could Change Biotech Forever, we drew over 40 comments. 

A tiny molecular machine used by bacteria to kill attacking viruses could change the way that scientists edit the DNA of plants, animals and fungi, revolutionizing genetic engineering. The protein, called Cas9, is quite simply a way to more accurately cut a piece of DNA.

“This could significantly accelerate the rate of discovery in all areas of biology, including gene therapy in medicine, the generation of improved agricultural goods, and the engineering of energy-producing microbes,” says Luciano Marraffini of Rockefeller University.

The ability to make modular changes in the DNA of bacteria and primitive algae has resulted in drug and biofuel companies such as Amyris and LS9. But figuring out how to make changes in the genomes of more complicated organisms has been tough.

http://www.forbes.com/sites/matthewherper/2013/03/19/the-protein-that-could-change-biotech-forever/?goback=.gde_48920_member_227143277

In this article we bring all the pieces to one place, telling the evolution of a series of discoveries, which together may have the Protein, Cas9,  changing the Biotech Industry forever with its contributions to Diagnosing Diseases and Gene Therapy by Precision Genome Editing and Cost-effective microRNA Profiling. 

MicroRNA detection on the cheap

MIT alumni’s startup provides rapid, cost-effective microRNA profiling, which is beneficial for diagnosing diseases.
Rob Matheson, MIT News Office
March 28, 2013
Current methods of detecting microRNA (miRNA) — gene-regulating molecules implicated in the onset of various diseases — can be time-consuming and costly: The custom equipment used in such tests costs more than $100,000, and the limited throughput of these systems further hinders progress.
Two MIT alumni are helping to rectify these issues through their fast-growing, Cambridge-headquartered startup, Firefly BioWorks Inc., which provides technology that allows for rapid miRNA detection in a large number of samples using standard lab equipment. This technology has helped the company thrive — and also has the potential to increase the body of research on miRNA, which could help lead to better disease diagnosis and screening.The company’s core technology, called Optical Liquid Stamping (OLS) — which was invented at MIT by Firefly co-founder and Chief Technical Officer Daniel C. Pregibon PhD ’08 — works by imprinting (or stamping) microparticle structures onto photosensitive fluids. The resulting three-dimensional hydrogel particles, encoded with unique “barcodes,” can be used for the detection of miRNAs across large numbers of samples. These particles are custom-designed for readout in virtually any flow cytometer, a cost-effective device that’s accessible to most scientists.“Our manufacturing process allows us to make very sophisticated particles that can be read on the most basic instruments,” says co-founder and CEO Davide Marini PhD ’03.The company’s first commercial product, FirePlex miRSelect, an miRNA-detection kit that uses an assay based on OLS-manufactured particles and custom software, began selling about a year ago. Since then, the company has drawn a steady influx of customers (primarily academic and clinical scientists) while seeing rapid revenue growth.

To date, most of the company’s revenue has come from backers who see value in Firefly’s novel technology. In addition to a cumulative $2.5 million awarded through Small Business Innovation Research grants — primarily from the National Cancer Institute — the company has attracted $3 million from roughly 20 independent investors. Its most recent funding came from a $500,000 grant from the Massachusetts Life Sciences Center.

Pregibon developed the technology in the lab of MIT chemical engineering professorPatrick Doyle, a Firefly co-founder who serves on the company’s scientific advisory board. Firefly’s intellectual property is partially licensed through the Technology Licensing Office at MIT, along with several other Firefly patents. Firefly’s technology, from OLS to miRNA detection, has been described in papers published in several leading journals, including ScienceNature MaterialsNature Protocols and Analytical Chemistry.

Shifting complexity from equipment to particle

The success of the technology, Marini says, derives from an early business decision to focus attention on the development of the hydrogel particle instead of the equipment needed. Essentially, this allowed the co-founders to focus on developing a high-quality miRNA assay and hit the market quickly with particles that are universally readable on basic lab instrumentation.

“Imagine sticking a microscopic barcode on a microscopic product,” Marini says. “How do you scan it? At the beginning we thought we would have to build our own scanner. This would have been an expensive proposition. Instead, by using a few clever tricks, we redesigned the barcode to make it readable by existing instruments. You can write these ‘barcodes,’ and all you need is one scanner to read different codes. To quote an investor: ‘It shifts the complexity from the equipment to the particle.’”

Firefly’s particles appear to a standard flow cytometer as a series of closely spaced cells; these data are recorded and the company’s FireCode software then regroups them into particle information, including miRNA target identification and quantity.

But why, specifically, did the company choose a flow cytometer as its primary “scanner”? Pregibon answers: “To start, there are nearly 100,000 cytometers worldwide. In addition, we are now seeing a trend where flow cytometers are getting smaller and closer to the bench — closer to the actual researcher. We’re finding that people are tight for money because of the economy and are trying to conserve capital as much as possible. In order to use our products, they can either buy a very inexpensive bench-top flow cytometer or use one that already exists in their core facility.”

In turn, opting out of equipment development and manufacturing costs has helped the company stay financially sound, says Marini, who worked in London’s financial sector before coming to MIT. As an additional perk, the manufacturers of flow cytometers have begun “courting” Firefly, Marini says, because “our products help expand the capability of their systems, which are now exclusively used to analyze cells.”

The company’s FirePlex kit allows researchers to assay (or analyze) roughly 70 miRNA targets simultaneously across 96 samples of a wide variety — including serum, plasma and crude cell digests — in approximately three hours.

This is actually a “middle-ground” assaying technique, Pregibon says, and saves researchers time and money: Until now, scientists were forced to use separate techniques to look at a few miRNA targets over thousands of samples, or vice versa.

Marini adds that if a scientist suspects a number of miRNAs, perhaps 50 or so, could be involved in a pancreatic-cancer pathway, the only way to know for sure is to test those 50 targets over hundreds of samples. “There’s nowhere to do this today in a cost-effective, timely manner. Our tech now allows that,” he says.

‘Over the bridge of validation’

Because miRNAs are so important in the regulation of genes, and ultimately proteins, they have implications in a broad range of diseases, from cancer to Alzheimer’s disease. Several studies have suggested these relationships, but the field currently lacks the validation required to definitively demonstrate clinical utility.

With that in mind, Pregibon hopes that Firefly’s technology will help push miRNA-based diagnoses “over the bridge of validation,” giving scientists the means to validate miRNA signatures they discover in diagnosing diseases such as cancer. “That’s where we want to fit in,” he says. “With the help of a technology like ours, you’ll start to see more tests hitting the market and ultimately, more people benefitting from early cancer detection.”

Firefly’s aim is to strengthen preventive medicine in the United States. “In the long term, we see these products helping in the shift from reactive to preventative medicine,” Marini says. “We believe we will see a proliferation of tools for detection of diseases. We want to move away from the system we have now, which is curing before it’s too late.”

Pregibon says Firefly’s technology can be used across several molecule classes that are important in development and disease research: proteins, messenger RNA and DNA, among many others. “Essentially, the possibilities are endless,” Pregibon says.

Editing the genome with high precision

New method allows scientists to insert multiple genes in specific locations, delete defective genes.
Anne Trafton, MIT News Office
 
Researchers at MIT, the Broad Institute and Rockefeller University have developed a new technique for precisely altering the genomes of living cells by adding or deleting genes. The researchers say the technology could offer an easy-to-use, less-expensive way to engineer organisms that produce biofuels; to design animal models to study human disease; and  to develop new therapies, among other potential applications.To create their new genome-editing technique, the researchers modified a set of bacterial proteins that normally defend against viral invaders. Using this system, scientists can alter several genome sites simultaneously and can achieve much greater control over where new genes are inserted, says Feng Zhang, an assistant professor of brain and cognitive sciences at MIT and leader of the research team.“Anything that requires engineering of an organism to put in new genes or to modify what’s in the genome will be able to benefit from this,” says Zhang, who is a core member of the Broad Institute and MIT’s McGovern Institute for Brain Research.Zhang and his colleagues describe the new technique in the Jan. 3 online edition ofScience. Lead authors of the paper are graduate students Le Cong and Ann Ran.Early effortsThe first genetically altered mice were created in the 1980s by adding small pieces of DNA to mouse embryonic cells. This method is now widely used to create transgenic mice for the study of human disease, but, because it inserts DNA randomly in the genome, researchers can’t target the newly delivered genes to replace existing ones.

In recent years, scientists have sought more precise ways to edit the genome. One such method, known as homologous recombination, involves delivering a piece of DNA that includes the gene of interest flanked by sequences that match the genome region where the gene is to be inserted. However, this technique’s success rate is very low because the natural recombination process is rare in normal cells.

More recently, biologists discovered that they could improve the efficiency of this process by adding enzymes called nucleases, which can cut DNA. Zinc fingers are commonly used to deliver the nuclease to a specific location, but zinc finger arrays can’t target every possible sequence of DNA, limiting their usefulness. Furthermore, assembling the proteins is a labor-intensive and expensive process.

Complexes known as transcription activator-like effector nucleases (TALENs) can also cut the genome in specific locations, but these complexes can also be expensive and difficult to assemble.

Precise targeting

The new system is much more user-friendly, Zhang says. Making use of naturally occurring bacterial protein-RNA systems that recognize and snip viral DNA, the researchers can create DNA-editing complexes that include a nuclease called Cas9 bound to short RNA sequences. These sequences are designed to target specific locations in the genome; when they encounter a match, Cas9 cuts the DNA.

This approach can be used either to disrupt the function of a gene or to replace it with a new one. To replace the gene, the researchers must also add a DNA template for the new gene, which would be copied into the genome after the DNA is cut.

Each of the RNA segments can target a different sequence. “That’s the beauty of this — you can easily program a nuclease to target one or more positions in the genome,” Zhang says.

The method is also very precise — if there is a single base-pair difference between the RNA targeting sequence and the genome sequence, Cas9 is not activated. This is not the case for zinc fingers or TALEN. The new system also appears to be more efficient than TALEN, and much less expensive.

The new system “is a significant advancement in the field of genome editing and, in its first iteration, already appears comparable in efficiency to what zinc finger nucleases and TALENs have to offer,” says Aron Geurts, an associate professor of physiology at the Medical College of Wisconsin. “Deciphering the ever-increasing data emerging on genetic variation as it relates to human health and disease will require this type of scalable and precise genome editing in model systems.”

The research team has deposited the necessary genetic components with a nonprofit called Addgene, making the components widely available to other researchers who want to use the system. The researchers have also created a website with tips and tools for using this new technique.

Engineering new therapies

Among other possible applications, this system could be used to design new therapies for diseases such as Huntington’s disease, which appears to be caused by a single abnormal gene. Clinical trials that use zinc finger nucleases to disable genes are now under way, and the new technology could offer a more efficient alternative.

The system might also be useful for treating HIV by removing patients’ lymphocytes and mutating the CCR5 receptor, through which the virus enters cells. After being put back in the patient, such cells would resist infection.

This approach could also make it easier to study human disease by inducing specific mutations in human stem cells. “Using this genome editing system, you can very systematically put in individual mutations and differentiate the stem cells into neurons or cardiomyocytes and see how the mutations alter the biology of the cells,” Zhang says.

In the Science study, the researchers tested the system in cells grown in the lab, but they plan to apply the new technology to study brain function and diseases.

The research was funded by the National Institute of Mental Health; the W.M. Keck Foundation; the McKnight Foundation; the Bill & Melinda Gates Foundation; the Damon Runyon Cancer Research Foundation; the Searle Scholars Program; and philanthropic support from MIT alumni Mike Boylan and Bob Metcalfe, as well as the newscaster Jane Pauley.

SOURCE:
Published online 2012 September 4. doi:  10.1073/pnas.1208507109
PMCID: PMC3465414
PNAS Plus

Cas9–crRNA ribonucleoprotein complex mediates specific DNA cleavage for adaptive immunity in bacteria

ABSTRACT

Clustered, regularly interspaced, short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems provide adaptive immunity against viruses and plasmids in bacteria and archaea. The silencing of invading nucleic acids is executed by ribonucleoprotein complexes preloaded with small, interfering CRISPR RNAs (crRNAs) that act as guides for targeting and degradation of foreign nucleic acid. Here, we demonstrate that the Cas9–crRNA complex of the Streptococcus thermophilus CRISPR3/Cas system introduces in vitro a double-strand break at a specific site in DNA containing a sequence complementary to crRNA. DNA cleavage is executed by Cas9, which uses two distinct active sites, RuvC and HNH, to generate site-specific nicks on opposite DNA strands. Results demonstrate that the Cas9–crRNA complex functions as an RNA-guided endonuclease with RNA-directed target sequence recognition and protein-mediated DNA cleavage. These findings pave the way for engineering of universal programmable RNA-guided DNA endonucleases.

Keywords: nuclease, site-directed mutagenesis, RNA interference, DNA interference

Comparison with Other RNAi Complexes

The mechanism proposed here for the cleavage of dsDNA by the Cas9–crRNA complex differs significantly from that for the type I-E (former “Ecoli”) system (7). In the E. coli type I-E system crRNA and Cas proteins assemble into a large ribonucleoprotein complex, Cascade, that facilitates target recognition by enhancing sequence-specific hybridization between the crRNA and complementary target sequences (7). Target recognition is dependent on the PAM and governed by the seed crRNA sequence located at the 5′ end of the spacer region (24). However, although the Cascade–crRNA complex alone is able to bind dsDNA containing a PAM and a protospacer, it requires an accessory Cas3 protein for DNA cleavage. Cas3 is an ssDNA nuclease and helicase that is able to cleave ssDNA, producing multiple cuts (10). It has been demonstrated recently that Cas3 degrades E. coli plasmid DNA in vitro in the presence of the Cascade–crRNA complex (25). Thus, current data clearly show that the mechanistic details of the interference step for the type I-E system differ from those of type II systems, both in the catalytic machinery involved and the nature of the molecular mechanisms.

In type IIIB CRISPR/Cas systems, present in many archaea and some bacteria, Cmr proteins and cRNA assemble into an effector complex that targets RNA (612). In Pyrococcus furiosus the RNA-silencing complex, comprising six proteins (Cmr1–Cmr6) and crRNA, binds to the target RNA and cleaves it at fixed distance from the 3′ end. The cleavage activity depends on Mg2+ ions; however, individual Cmr proteins responsible for target RNA cleavage have yet to be identified. The effector complex of Sulfolobus solfataricus, comprising seven proteins (Cmr1–Cmr7) and crRNA, cuts invading RNA in an endonucleolytic reaction at UA dinucleotides (13). Importantly, these two archaeal Cmr–crRNA complexes perform RNA cleavage in a PAM-independent manner.

Overall, we have shown that the Cas9–crRNA complex in type II CRISPR/Cas systems is a functional homolog of Cascade in type I systems and represents a minimal DNAi complex. The simple modular organization of the Cas9–crRNA complex, in which specificity for DNA targets is encoded by crRNAs and the cleavage enzymatic machinery is brought by a single, multidomain Cas protein, provides a versatile platform for engineering universal RNA-guided DNA endonucleases. Indeed, by altering the RNA sequence within the Cas9–crRNA complex, programmable endonucleases can be designed both for in vitro and in vivo applications. To provide proof of principle of such a strategy, we engineered de novo into a CRISPR locus a spacer targeted to a specific sequence on a plasmid and demonstrated that such a plasmid is cleaved by the Cas9–crRNA complex at a sequence specified by the designed crRNA. Experimental demonstration that RuvC and HNH active-site mutants of Cas9 are functional as strand-specific nicking enzymes opens the possibility of generating programmed DNA single-strand breaks de novo. Taken together, these findings pave the way for the development of unique molecular tools for RNA-directed DNA surgery.

SOURCE:

Cheap and easy technique to snip DNA could revolutionize gene therapy

By Robert Sanders, Media Relations | January 7, 2013

BERKELEY —A simple, precise and inexpensive method for cutting DNA to insert genes into human cells could transform genetic medicine, making routine what now are expensive, complicated and rare procedures for replacing defective genes in order to fix genetic disease or even cure AIDS.

Cas9 protein on DNA
The bacterial enzyme Cas9 is the engine of RNA-programmed genome engineering in human cells. Graphic by Jennifer Doudna/UC Berkeley.
IMAGE SOURCE:

Discovered last year by Jennifer Doudna and Martin Jinek of the Howard Hughes Medical Institute and University of California, Berkeley, and Emmanuelle Charpentier of the Laboratory for Molecular Infection Medicine-Sweden, the technique was labeled a “tour de force” in a 2012 review in the journal Nature Biotechnology.

That review was based solely on the team’s June 28, 2012, Science paper, in which the researchers described a new method of precisely targeting and cutting DNA in bacteria.

Two new papers published last week in the journal Science Express demonstrate that the technique also works in human cells. A paper by Doudna and her team reporting similarly successful results in human cells has been accepted for publication by the new open-access journal eLife.

“The ability to modify specific elements of an organism’s genes has been essential to advance our understanding of biology, including human health,” said Doudna, a professor of molecular and cell biology and of chemistry and a Howard Hughes Medical Institute Investigator at UC Berkeley. “However, the techniques for making these modifications in animals and humans have been a huge bottleneck in both research and the development of human therapeutics.

“This is going to remove a major bottleneck in the field, because it means that essentially anybody can use this kind of genome editing or reprogramming to introduce genetic changes into mammalian or, quite likely, other eukaryotic systems.”

“I think this is going to be a real hit,” said George Church, professor of genetics at Harvard Medical School and principal author of one of the Science Express papers. “There are going to be a lot of people practicing this method because it is easier and about 100 times more compact than other techniques.”

“Based on the feedback we’ve received, it’s possible that this technique will completely revolutionize genome engineering in animals and plants,” said Doudna, who also holds an appointment at Lawrence Berkeley National Laboratory. “It’s easy to program and could potentially be as powerful as the Polymerase Chain Reaction (PCR).”

The latter technique made it easy to generate millions of copies of small pieces of DNA and permanently altered biological research and medical genetics.

Cruise missiles

Two developments – zinc-finger nucleases and TALEN (Transcription Activator-Like Effector Nucleases) proteins – have gotten a lot of attention recently, including being together named one of the top 10 scientific breakthroughs of 2012 by Science magazine. The magazine labeled them “cruise missiles” because both techniques allow researchers to home in on a particular part of a genome and snip the double-stranded DNA there and there only.

Researchers can use these methods to make two precise cuts to remove a piece of DNA and, if an alternative piece of DNA is supplied, the cell will plug it into the cut instead. In this way, doctors can excise a defective or mutated gene and replace it with a normal copy. Sangamo Biosciences, a clinical stage biospharmaceutical company, has already shown that replacing one specific gene in a person infected with HIV can make him or her resistant to AIDS.

Both the zinc finger and TALEN techniques require synthesizing a large new gene encoding a specific protein for each new site in the DNA that is to be changed. By contrast, the new technique uses a single protein that requires only a short RNA molecule to program it for site-specific DNA recognition, Doudna said.

In the new Science Express paper, Church compared the new technique, which involves an enzyme called Cas9, with the TALEN method for inserting a gene into a mammalian cell and found it five times more efficient.

“It (the Cas9-RNA complex) is easier to make than TALEN proteins, and it’s smaller,” making it easier to slip into cells and even to program hundreds of snips simultaneously, he said. The complex also has lower toxicity in mammalian cells than other techniques, he added.

“It’s too early to declare total victory” over TALENs and zinc-fingers, Church said, “but it looks promising.”

Based on the immune systems of bacteria

Doudna discovered the Cas9 enzyme while working on the immune system of bacteria that have evolved enzymes that cut DNA to defend themselves against viruses. These bacteria cut up viral DNA and stick pieces of it into their own DNA, from which they make RNA that binds and inactivates the viruses.

UC Berkeley professor of earth and planetary science Jill Banfield brought this unusual viral immune system to Doudna’s attention a few years ago, and Doudna became intrigued. Her research focuses on how cells use RNA (ribonucleic acids), which are essentially the working copies that cells make of the DNA in their genes.

Doudna and her team worked out the details of how the enzyme-RNA complex cuts DNA: the Cas9 protein assembles with two short lengths of RNA, and together the complex binds a very specific area of DNA determined by the RNA sequence. The scientists then simplified the system to work with only one piece of RNA and showed in the earlier Science paper that they could target and snip specific areas of bacterial DNA.

“The beauty of this compared to any of the other systems that have come along over the past few decades for doing genome engineering is that it uses a single enzyme,” Doudna said. “The enzyme doesn’t have to change for every site that you want to target – you simply have to reprogram it with a different RNA transcript, which is easy to design and implement.”

The three new papers show this bacterial system works beautifully in human cells as well as in bacteria.

“Out of this somewhat obscure bacterial immune system comes a technology that has the potential to really transform the way that we work on and manipulate mammalian cells and other types of animal and plant cells,” Doudna said. “This is a poster child for the role of basic science in making fundamental discoveries that affect human health.”

Doudna’s coauthors include Jinek and Alexandra East, Aaron Cheng and Enbo Ma of UC Berkeley’s Department of Molecular and Cell Biology.

Doudna’s work was sponsored by the Howard Hughes Medical Institute.

RELATED INFORMATION

SOURCE:
http://newscenter.berkeley.edu/2013/01/07/cheap-and-easy-technique-to-snip-dna-could-revolutionize-gene-therapy/

Matthew Herper, Forbes Staff on 3/24/2013

 A Cancer Patient’s Quest Hits DNA Pay Dirt

 

Kathy Giusti

Kathy Giusti has faced her cancer with the verve of an entrepreneur. Now her fight with multiple myeloma has moved to a new front: DNA.

Giusti was a 37-year-old marketing executive at Searle (now part of Pfizer) when she was diagnosed in 1996 with myeloma, a deadly blood and bone marrow cancer. She had a 1-year-old daughter. Sixty percent of myeloma patients die within five years, but Giusti beat the odds, living for a decade and a half through multiple rounds of drug therapy and a bone marrow transplant from her twin sister.

She has also changed the way her disease is treated. Giusti founded an advocacy group, the Multiple Myeloma Research Foundation, that works with companies like NovartisCelgene, and Merck to develop new treatments. It played a key role in the development of Velcade and Revlimid, two of the biggest advances in treating the disease, which is diagnosed in 20,000 patients a year.

Now a new research effort, funded with $14 million of MMRF money, has revealed new hints at what causes the disease and potential avenues for treating it. “This is going to be the next wave of how health care gets changed over time,” Giusti says. The results are published in the current issue of Nature.

Working with patient samples collected by the MMRF and using DNA sequencers made by Illumina of San Diego, researchers at the Broad Institute of MIT and Harvard sequenced the genes of 38 myeloma tumors and the DNA of the patients in whom they were growing. Tumors are twisted versions of the people in which they are growing; their DNA is mutated and disfigured, turning them deadly. By comparing DNA from healthy cells with malignant ones, researchers can find genetic differences that might be what led the tumors to go bad in the first place.

This experiment would have been unthinkable just a few years ago, when sequencing a human being was so expensive that all the people whose DNA had been read out could fit in a small room. In 2005, the idea of producing 38 DNA sequences was laughable. Now it’s par for the course, and researchers expect thousands of genomes will be sequenced by the end of the year – and experiments like this are expected to become commonplace.

What’s so exciting is that sometimes the DNA changes scientists find are completely unexpected. “There were genes we found to be recurrently mutated and yet no one had any clue that they had anything to do with multiple myeloma or any other cancer,” says Todd Golub, the Broad researcher who led the study. He splits his time with the Dana-Farber Cancer Institute.

One gene, called FAM46C, was mutated in 13% of the cancers, but has never been studied in humans. “It appears no one had been working on it,” says Golub, but from studies in yeast and bacteria it appears that it has to do with how the recipes in genes are used to make proteins, the building blocks of just about everything in the body.

Another surprise gene, called BRAF, is generating excitement because it is the target of a skin cancer drug developed by Plexxikon, a small biotech firm that is partnered with Roch and is being purchased by Daiichi Sankyo. For the 4% of myeloma patients who have this mutation, this drug might be an option. The challenge will be testing it: it will be difficult to find enough of these patients to conduct a clinical trial. The MMRF says early discussions on such a study are moving forward. Giusti imagines that in the future, the MMRF may fund studies not of myeloma, but of a mix of different cancers caused by similar genetic mutations.

Several of the genes seem involved in the proteins that help guide epigenetics, a kind of molecular code written on DNA that may represent another kind of genetic code. The MMRF is already supporting some small drug companies that hope to create cancer drugs that target this second code.

Golub, the Broad scientist, says that right now it doesn’t make sense for most multiple myeloma patients to get their full DNA sequences outside of clinical trials, although he can imagine that for patients who have failed every available treatment it might make sense as a way to come up with another drug to try.

Giusti says, however, that the kinds of genetic tests that are done are changing the way that patients understand their disease. “Patients like me are starting to know, ‘I have this DNA translocation, maybe a proteasome inhibitor [a type of drug] is better for me.’ We become forerunners in the role patient can plan and the importance it has in drug development.”

Moving past old ways of thinking about inventing new medicines to a new path that is based on genetics and a flood of biological data is going to be difficult. But Giusti has never been afraid of hard — and she is sure there will be ways to drive the science forward.

SOURCE:

http://www.forbes.com/sites/matthewherper/2011/03/24/a-cancer-patients-quest-hits-dna-pay-dirt/

REFERENCES

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465414/

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Reporter: Aviva Lev-Ari, PhD, RN

Track 6: Systems Pharmacology

Track 6 focuses on how compounds (drugs) work in the body. How are they influenced by various ‘omics’? How do they vary by tissue? The practical implications of such a compound-centric approach are exciting: new targets, new screens, new markers, new understanding of drug failure mechanisms. The systems computational tool sets including multi-scale modeling, simulation, web-based platforms, etc. will be emphasized.

Final Agenda

Download Brochure | Pre-Conference Workshops

TUESDAY, APRIL 9

7:00 am Workshop Registration and Morning Coffee

8:00 Pre-Conference Workshops*

*Separate Registration Required

2:00 – 7:00 pm Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge Healthtech Institute

4:05 Keynote Introduction

Kevin Brode, Senior Director, Health & Life Sciences, Americas Hitachi Data Systems

» 4:15 PLENARY KEYNOTE

Do Network Pharmacologists Need Robot Chemists?

Andrew HopkinsAndrew L. Hopkins, DPhil, FRSC, FSB, Division of Biological Chemistry and Drug Design, College of Life Sciences, University of Dundee

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OKTA5:00 Welcome Reception in the Exhibit Hall with Poster Viewing
Welcome Reception Introduction, Sponsored by Okta

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WEDNESDAY, APRIL 10

7:00 am Registration and Morning Coffee

8:00 Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:05 Keynote Introduction

Sanjay Joshi, CTO, Life Sciences, EMC Isilon

» 8:15 PLENARY KEYNOTE

Atul ButteAtul Butte, M.D., Ph.D., Division Chief and Associate Professor, Stanford University School of Medicine; Director, Center for Pediatric Bioinformatics, Lucile Packard Children’s Hospital; Co-founder, Personalis and Numedii

8:55 Benjamin Franklin Award & Laureate Presentation

9:15 Best Practices Award Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

PHARMACODYNAMIC MODELS

10:50 Chairperson’s Remarks

Hugo Geerts, Ph.D., CSO, Computational Neuropharmacology, In Silico Biosciences

» Featured Speaker

11:00 Systems Pharmacology in a Post-Genomic Era

Peter Sorger, Ph.D., Professor, Systems Biology, Harvard Medical School; Co-Chair, Harvard Initiative in Systems Pharmacology

I will describe the emergence of “systems pharmacology” as a means to guide the creation of new molecular matter, study cellular networks and their perturbation by drugs, understand pharmaco-kinetics and pharmaco-dynamics in mouse and man and design and analyze clinical trial data. The approach combines mathematical modeling with empirical measurement as a means to tackle basic and clinical problems in pharmacology. Ultimately we aim for models that describe drug responses at multiple temporal and physical scales from molecular mechanism to whole-organism physiology.

11:30 Using Quantitative Systems Pharmacology for De-Risking Projects in CNS R&D

Hugo Geerts, Ph.D., CSO, Computational Neuropharmacology, In Silico Biosciences

Quantitative Systems Pharmacology is a computer based mechanistic modeling approach combining physiology, the functional imaging of genetics with the pharmacology of drug-receptor interaction and parameterized with clinical data and is a possible powerful tool for improving the success rate of CNS R&D projects. The presentation will include failure analyses of unsuccessful clinical trials, correct prospective identification of clinical problems that halted clinical development and estimation of genotype effects on the pharmacodynamics of candidate drugs.

Thomson Reuters logo12:00 pm Systems Pharmacology Approaches to Drug Repositioning

Svetlana Bureeva, Ph.D., Director, Professional Services, Thomson Reuters, IP & Science

Drug repositioning requires advanced computational approaches and comprehensive knowledgebase information to reach success. Thomson Reuters will present on recent advances in drug repositioning approaches, their validation and performance, best practices in using systems biology content, and successful case studies.

12:30 Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

HIGH CONTENT ANALYSIS: CANCER CELL LINES

1:40 Chairperson’s Remarks

William Reinhold, Manager, Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology (LMP), National Cancer Institute (NCI)

1:45 Systems Pharmacology Using CellMiner and the NCI-60 Cancerous Cell Lines

William Reinhold, Manager, Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology (LMP), National Cancer Institute (NCI)

CellMiner is a web-based application that allows rapid access to and comparison between 20,503 compound activities and the expression levels of 26,065 genes and 360 microRNAs. Included are 102 FDA-approved drugs as well as 53 in clinical trials. The tool is designed for the non-informatisist, and allows the user wide latitude in defining the question of interest. This opens the door to systems pharmacological studies for physicians, molecular biologists and others without bioinformatics expertise.

2:15 Oncology Drug Combinations at Novartis

Joseph Lehár, Ph.D., Associate Director, Bioinformatics, Oncology Translational Research, Novartis; Adjunct Assistant Professor, Bioinformatics, Boston University

Novartis is undertaking a large-scale effort to comprehensively describe cancer through the lens of cell cultures and tissue samples.  In collaboration with academic and industrial partners, we have generated mutation status, gene copy number, and gene expression data for a library of 1,000 cancer cell lines, representing most cancer lineages and common genetic backgrounds.  Most of these cell lines have been tested for chemosensitivity against ~1,200 cancer-relevant compounds, and we are systematically exploring drug combinations for synergy against ~100 prioritized CCLE lines.  We expect this large-scale campaign to enable efficient patient selection for clinical trials on existing cancer drugs, reveal many therapeutically promising drug synergies or anti-resistance combinations, and provide unprecedented detail on functional interactions between cancer signaling pathways.   I will discuss early highlights of this work and describe our plans to make use of this resource.

2:45 Sponsored Presentations (Opportunities Available)

3:15 Refreshment Break in the Exhibit Hall with Poster Viewing

PHARMACODYNAMIC MODELS FOR ONCOLOGY

3:45 Systems Biology in Cancer Immunotherapy: Applications in the Understanding of Mechanism of Action and Therapeutic Response

Debraj Guha Thakurta, Ph.D., Senior Scientist II & Group Leader, Systems Biology, Dendreon Corporation

We are using high-content platforms (DNA and protein microarrays, RNA-seq) in various stages of the development of cellular immunotherapies for cancer. We will provide examples of genomic applications that can aid in the mechanistic understanding and the discovery of molecular markers associated with the efficacy of a cancer immunotherapy..

4:15 Use of Systems Pharmacology to Aid Cancer Clinical Development

Anna Georgieva Kondic, Ph.D., MBA, Senior Principal Scientist, Modeling and Simulation, Merck Research Labs

The last few years have seen an increased use of physiologically-based pharmacokinetics and pharmacodynamics models in Oncology drug development. This is partially due to an improved mechanistic understanding of disease drivers and the collection of better patient-level quantitative data that lends itself to modeling. In this talk, a suite of studies where systems modeling was successfully used to inform either preclinical to clinical transition or clinical study design will be presented. The talk will complete with a potential systems pharmacology framework that can be used systematically in drug development.

4:45 Two-Edged Sword Role of the Mammalian DNA Methyltransferases: New Implication to Cancer Therapy Targeting the Epigenetic Pathway

Che-Kun James Shen, Ph.D., Distinguished Research Fellow, Institute of Molecular Biology, Academia Sinica

Methylation at the 5-position of cytosine (C) to generate 5-methylcytosine (5-mC) on the vertebrate genomes is an essential epigenetic modification that regulates different biological processes including carcinogenesis. This modification has been known to be accomplished by the combined catalytic actions of three DNA methyltransferases (DNMTs), the de novo enzymes DNMT3A/ DNMT3B and the maintenance enzyme DNMT1. This property of DNMTs and the imbalance of CpG methylation in cancer cells have led to the development of cancer therapeutic drugs/ chemicals targeting the DNA methylation activities of DNMTs. However, we have recently discovered that the mammalian DNMTs could also act as active DNA 5-mC demethylases in a Ca++ion-and redox state-dependent manner. This suggests new directions for re-investigation of the structures of DNMTs and their functions in the genome wide and/or local DNA methylation in the mammalian cells. In particular, the concept and strategies for drug therapy targeting the DNMTs may need to be re-evaluated.

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes

Thursday, April 11

7:00 am Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee

MODELING AND MINING TARGETS

8:45 Chairperson’s Opening Remarks

I-Ming Wang, Ph.D., Associate Scientific Director, Research Solutions and Bioinformatics, Informatics and Analysis, Merck Research Laboratory

8:50 Systems Biology Approach for Identification of New Targets and Biomarkers

I-Ming Wang, Ph.D., Associate Scientific Director, Research Solutions and Bioinformatics, Informatics and Analysis, Merck Research Laboratory

A representative gene signature was identified by an integrated analysis of expression data in twelve rodent inflammatory models/tissues. This “inflammatome” signature is highly enriched in known drug target genes and is significantly overlapped with macrophage-enriched metabolic networks (MEMN) reported previously. A large proportion of genes in this signature are tightly connected in several tissue-specific Bayesian networks built from multiple mouse F2 crosses and human tissue cohorts; furthermore, these tissue networks are very significantly overlapped. This indicates that variable expression in this set of co-regulated genes is the main driver of many disease states. Disease-specific gene sets with the potential of being utilized as biomarkers were also identified with the approach we applied. The identification of this “inflammatome” gene signature extends the coverage of MEMN beyond adipose and liver in the metabolic disease to multiple diseases involving various affected tissues.

9:20 Optimizing Therapeutic Index (TI) by Exploring Co-Dependencies of Target and Therapeutic Properties

Madhu Natarajan, Ph.D., Associate Director, Computational Biology, Discovery Research, Shire HGT

Conventional drug-discovery informatics workflows employ combinations of mechanistic/probabilistic in-silico methods to rank lists of targets; therapeutics are then developed for “optimal” targets. I describe a systems pharmacology approach that instead integrates systematic in-silico therapeutic perturbation with models of target/disease biology to identify conditions for optimal TI; non-intuitively optimal TI is sometimes achieved by pairing sub-optimal targets with therapeutics having appropriate properties.

9:50 Leveraging Mathematical Models to Understand Population Variability in Response to Cardiac Drugs

Eric Sobie, Ph.D., Associate Professor, Pharmacology & Systems Therapeutics, Icahn School of Medicine, Mount Sinai School of Medicine

Mathematical models of heart cells and tissues are sufficiently advanced that the models can predict mechanisms underlying pro-arrhythmic or anti-arrhythmic effects of drugs. At present, however, these models are not adequate for understanding variability across a population, i.e., why a drug may be effective in one patient but ineffective in another patient. I will describe novel computational approaches my laboratory has developed to quantify and predict differences between individuals in response to cardiac drugs.

10:20 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

10:45 Plenary Keynote Panel Chairperson’s Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:50 Plenary Keynote Panel Introduction

Yury Rozenman, Head of BT for Life Sciences, BT Global Services

» PLENARY KEYNOTE PANEL

11:05 The Life Sciences CIO Panel

Panelists:
Remy Evard, CIO, Novartis Institutes for BioMedical Research
Martin Leach, Ph.D., Vice President, R&D IT, Biogen Idec
Andrea T. Norris, Director, Center for Information Technology (CIT) and Chief Information Officer, NIH
Gunaretnam (Guna) Rajagopal, Ph.D., VP & CIO – R&D IT, Research, Bioinformatics & External Innovation, Janssen Pharmaceuticals
Cris Ross, Chief Information Officer, Mayo Clinic

12:15 pm Luncheon in the Exhibit Hall with Poster Viewing

MODELING MOLECULAR AND PATHOPHYSIOLOGICAL DATA

1:55 Chairperson’s Remarks

Jake Chen, Ph.D., Associate Professor, Indiana University School of Informatics & Purdue University Department of Computer Science; Director, Indiana Center for Systems Biology and Personalized Medicine

2:00 Predicting Adverse Side Effects of Drugs Using Systems Pharmacology

Jake Chen, Ph.D., Associate Professor, Indiana University School of Informatics & Purdue University Department of Computer Science; Director, Indiana Center for Systems Biology and Personalized Medicine

A new way of studying drug toxicity is to incorporate biomolecular annotation and network data with clinical observations of drug targets upon drug perturbations. I will describe the development of a novel computational modeling framework, with which we demonstrated the highest drug toxicity prediction accuracies ever reported by far. Adoption of this framework may have profound practical drug discovery implications.

2:30 Holistic Integration of Molecular and Physiological Data and Its Application in Personalized Healthcare

David de Graaf, Ph.D. President and CEO, Selventa

There are multiple industry-wide challenges in aggregating molecular and pathophysiological data for systems pharmacology to transform the process of drug discovery and development. One of the ways to address these challenges is to utilize a common computable biological expression language (BEL) that can provide a comprehensive knowledge network for new discoveries. An application of BEL and its use in identifying clinically relevant predictive biomarkers for patient stratification will be presented.

3:00 The Role of Informatics in ADME Pharmacogenetics

Boyd SteereBoyd Steere, Ph.D., Senior Research Scientist, Lilly Research Laboraories, IT Research Informatics, Eli Lilly

The leveraging of pharmacogenetics to support decisions in early-phase clinical trial design requires informatics methods to integrate, visualize, and analyze heterogeneous data sets from many different discovery platforms.  This presentation describes challenges and solutions in making sense of diverse sets of genetic, protein, and metabolic data in support of ADME pharmacology projects.

3:30 A Systems Pharmacology Approach to Understand and Optimize Functional Selectivity for Non-Selective Drugs

Joshua Apgar, Principal Scientist, Systems Biology, Dept. of Immunology & Inflammation, Boehringer Ingelheim Pharmaceuticals, Inc.

Most commonly the selectivity of a compound is defined in an in vitro or cellular assay, and it is thought of as principally a function of the binding energy of the drug to its on-target and off-target proteins; however, in vivo functional selectivity is much more complicated, and is affected by systems level effects such as multiple feedback processes within and between the various on- and off-target pathways. These systems level processes are often impossible to reconstruct in vitro as they involve many cell types, tissues, and organs systems throughout the body. We show here that through mathematical modeling we were able to identify, in silico, molecular properties that are critical to driving functional selectivity. The models, although simple, capture the key systems pharmacology needed to understand the on- an off- target effects. Surprisingly, in this case, the key driver of functional selectivity is not the affinity of the drugs but rather the pharmacokinetics, with drugs having a short half-life predicted to be the most functionally selective.

4:00 Conference Adjourns


CONCURRENT TRACKS
Track 1: IT Infrastructure – Hardware
Big Data Solutions and End-User Perspectives
Track 7: eClinical Trials Solutions
Innovative Management in Clinical Trials
Track 2: Software Development
Technologies and Applications for Managing and Sharing Data
NEW THIS YEAR!
Track 8: Data Visualization and Exploration Tools
From Discovery to the Clinic
Track 3: Cloud Computing
Riding the Cloud to Next-Generation Computing
Track 9: Drug Discovery Informatics
Thinking of Drugs Outside of the Box
Track 4: Bioinformatics
Understanding Massive Quantities of -omic Information across Research Initiatives
NEW THIS YEAR!
Track 10: Clinical OmicsTools for Integrating and Interrogating Multiple ‘Omic Data Sets 
Track 5: Next-Generation Sequencing Informatics
NGS, Genome-Scale Screening and HTP Proteomics
Track 11: Collaborations and Open Access Innovations
Collaborative and Open Access Models for Advancing Research, Discovery and Personalized Medicine
Track 6: Systems Pharmacology
Pathways to Patient Response
Track 12: Cancer Informatics
Applying Computational Biology to Cancer Research/Care

WORKSHOPS – VIEW DETAILS
Morning Workshops
  • Integrated Research Data Management
  • Quality Practices for R&D Informatics
  • Beyond the Cloud
  • IT & Informatics in Support of Collaboration and Externalization
  • The Repurposing Challenge
Afternoon Workshops
  • Avoiding Intellectual Property Problems in Research Collaborations Using Information Technology
  • Avoiding Cloud Gotchas
  • Advancing the Use of EHR/EMR for Clinical Research and Drug Development
  • Cloud Computing in Hospital Data Management and Integration
  • Data Visualization in Biology: From the Basics to Big Data
  • Software for Clinical Genomics
  • IT Project Planning and Implementation

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  • And Much More!
KEYNOTE PRESENTERS:

Atul ButteAtul Butte, M.D., Ph.D., Division Chief and Associate Professor, Stanford University School of Medicine; Director, Center for Pediatric Bioinformatics, Lucile Packard Children’s Hospital; Co-founder, Personalis and Numedii

Andrew HopkinsAndrew L. Hopkins, D.Phil, FRSC, FSB, Division of Biological Chemistry and Drug Design, College of Life Sciences, University of Dundee

PLENARY SESSION:

The Life Sciences CIO Panel

From managing big data and cloud computing capabilities to building virtual communities and optimizing drug development, the life sciences CIO has to be a firefighter, evangelist, visionary. In this special plenary roundtable, Bio-IT World invites a select group of CIOs from big pharma, academia and government to discuss the major issues facing today’s biosciences organization and the prospects for future growth and organizational success.

Special guests:
Remy Evard – CIO, Novartis Institutes for BioMedical Research
Martin Leach, Ph.D., Vice President, R&D IT, Biogen Idec
Andrea T. Norris – Director, Center for Information Technology (CIT) and CIO, NIH
Gunaretnam (Guna) Rajagopal, Ph.D., VP & CIO – R&D IT, Research, Bioinformatics & External Innovation, Janssen Pharmaceuticals
Cris Ross – CIO, Mayo Clinic

FEATURED SESSIONS:

Managing Big Data: The Genome Center Perspective

Panelists Include: Matthew Trunnell (Broad Institute)
Alexander (Sasha) Wait Zaranek, (Harvard Medical School/Clinical Future, Inc.)
Guy Coates (The Wellcome Trust Sanger Institute)

Building the IT Architecture of the New York Genome Center

Chris Dwan, Acting Senior Vice President, Information Technology and Research Computing, New York Genome Center
Kevin Shianna, Senior Vice President, Sequencing Operations, New York Genome Center
Jim Harding, CTO, Sabey Corporation
Sanjay Joshi, CTO, Life Sciences, EMC Isilon Storage Division

Robert B. Darnell, M.D., Ph.D., President & Scientific Director, New York Genome Center

Additional Speakers to be Announced

  

3/4
VIDEO CHANNEL
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Bio-IT World Expo 2012 – 10th Anniversary Celebration
ClearTrial wins Best of Show 2012
CERF wins Best of Show 2012
OpsCode wins Best of Show 2012
Cambridge Semantics wins Best of Show 2012
Stephen Wolfram, Ph.D., part 1 – Keynote Presentation
BlueArc at 2011 Bio-IT World Conference & Expo
Roche innovative multi-touch environment for scientific decision
Praxeon DocumentLens
Yury Rozenman – Bio-IT World Expo 2011 Keynote Panel
Mark Boguski – Bio-IT World Expo 2011 Keynote Panel
Ken Buetow – Bio-IT World Expo 2011 Keynote Panel
Benjamin Heywood – Bio-IT World Expo 2011 Keynote Panel
Debora Goldfarb – Bio-IT World Expo 2011 Keynote Panel
Martin Leach – Bio-IT World Expo 2011 Keynote Panel
Jonathan Eisen – Ben Franklin Award 2011
Bryn Roberts part 1- Keynote Presentation

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Reporter: Aviva Lev-Ari, PhD, RN

 

Systems Pharmacology: Pathways to Patient Response @ BioIT World, Boston, MA World Trade Center, April 9-11, 2013

Conference Tracks:

IT Infrastructure – Hardware

Software Development

Cloud Computing

Bioinformatics

Next-Gen Sequencing Informatics

Systems Pharmacology

eClinical Trials Solutions

Data Visualization NEW!

Drug Discovery Informatics

Clinical Omics NEW!

Collaborations and Open

Access Innovations

Cancer Informatics

 

Track 6 focuses on how compounds (drugs) work in the body. How are they influenced by various ‘omics’? How do they vary by tissue? The practical implications of such a compound-centric approach are exciting: new targets, new screens, new markers, new understanding of drug failure mechanisms. The systems computational tool sets including multi-scale modeling, simulation, web-based platforms, etc. will be emphasized.

Final Agenda

 

Download Brochure | Pre-Conference Workshops

 

TUESDAY, APRIL 9

7:00 am Workshop Registration and Morning Coffee

8:00 Pre-Conference Workshops*

 

*Separate Registration Required

2:00 – 7:00 pm Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge Healthtech Institute

4:05 Keynote Introduction

Speaker to be Announced, Hitachi Data Systems

 

» 4:15 PLENARY KEYNOTE

Do Network Pharmacologists Need Robot Chemists?

Andrew HopkinsAndrew L. Hopkins, DPhil, FRSC, FSB, Division of Biological Chemistry and Drug Design, College of Life Sciences, University of Dundee

 

5:00 Welcome Reception in the Exhibit Hall with Poster Viewing

Drop off a business card at the CHI Sales booth for a chance to win 1 of 2 iPads® or 1 of 2 Kindle Fires®!*

*Apple ® and Amazon are not sponsors or participants in this program

 

WEDNESDAY, APRIL 10

7:00 am Registration and Morning Coffee

8:00 Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:05 Keynote Introduction

Sanjay Joshi, CTO, Life Sciences, EMC Isilon

 

» 8:15 PLENARY KEYNOTE

Atul ButteAtul Butte, M.D., Ph.D., Division Chief and Associate Professor, Stanford University School of Medicine; Director, Center for Pediatric Bioinformatics, Lucile Packard Children’s Hospital; Co-founder, Personalis and Numedii

 

8:55 Benjamin Franklin Award & Laureate Presentation

9:15 Best Practices Award Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

 

PHARMACODYNAMIC MODELS

10:50 Chairperson’s Remarks

» Featured Speaker

11:00 Systems Pharmacology in a Post-Genomic Era

Peter Sorger, Ph.D., Professor, Systems Biology, Harvard Medical School; Co-Chair, Harvard Initiative in Systems Pharmacology

I will describe the emergence of “systems pharmacology” as a means to guide the creation of new molecular matter, study cellular networks and their perturbation by drugs, understand pharmaco-kinetics and pharmaco-dynamics in mouse and man and design and analyze clinical trial data. The approach combines mathematical modeling with empirical measurement as a means to tackle basic and clinical problems in pharmacology. Ultimately we aim for models that describe drug responses at multiple temporal and physical scales from molecular mechanism to whole-organism physiology.

11:30 Using Quantitative Systems Pharmacology for De-Risking Projects in CNS R&D

Hugo Geerts, Ph.D., CSO, Computational Neuropharmacology, In Silico Biosciences

Quantitative Systems Pharmacology is a computer based mechanistic modeling approach combining physiology, the functional imaging of genetics with the pharmacology of drug-receptor interaction and parameterized with clinical data and is a possible powerful tool for improving the success rate of CNS R&D projects. The presentation will include failure analyses of unsuccessful clinical trials, correct prospective identification of clinical problems that halted clinical development and estimation of genotype effects on the pharmacodynamics of candidate drugs.

Thomson Reuters logo12:00 pm Systems Pharmacology Approaches to Drug Repositioning

Svetlana Bureeva, Ph.D., Director, Professional Services, Thomson Reuters, IP & Science

Drug repositioning requires advanced computational approaches and comprehensive knowledgebase information to reach success. Thomson Reuters will present on recent advances in drug repositioning approaches, their validation and performance, best practices in using systems biology content, and successful case studies.

12:30 Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

 

HIGH CONTENT ANALYSIS: CANCER CELL LINES

1:40 Chairperson’s Remarks

1:45 Systems Pharmacology Using CellMiner and the NCI-60 Cancerous Cell Lines

William Reinhold, Manager, Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology (LMP), National Cancer Institute (NCI)

CellMiner is a web-based application that allows rapid access to and comparison between 20,503 compound activities and the expression levels of 26,065 genes and 360 microRNAs. Included are 102 FDA-approved drugs as well as 53 in clinical trials. The tool is designed for the non-informatisist, and allows the user wide latitude in defining the question of interest. This opens the door to systems pharmacological studies for physicians, molecular biologists and others without bioinformatics expertise.

2:15 Oncology Drug Combinations at Novartis

Joseph Lehár, Ph.D., Associate Director, Bioinformatics, Oncology Translational Research, Novartis; Adjunct Assistant Professor, Bioinformatics, Boston University

Novartis is undertaking a large-scale effort to comprehensively describe cancer through the lens of cell cultures and tissue samples.  In collaboration with academic and industrial partners, we have generated mutation status, gene copy number, and gene expression data for a library of 1,000 cancer cell lines, representing most cancer lineages and common genetic backgrounds.  Most of these cell lines have been tested for chemosensitivity against ~1,200 cancer-relevant compounds, and we are systematically exploring drug combinations for synergy against ~100 prioritized CCLE lines.  We expect this large-scale campaign to enable efficient patient selection for clinical trials on existing cancer drugs, reveal many therapeutically promising drug synergies or anti-resistance combinations, and provide unprecedented detail on functional interactions between cancer signaling pathways.   I will discuss early highlights of this work and describe our plans to make use of this resource.

2:45 Sponsored Presentations (Opportunities Available)

3:15 Refreshment Break in the Exhibit Hall with Poster Viewing

 

PHARMACODYNAMIC MODELS FOR ONCOLOGY

3:45 Systems Biology in Cancer Immunotherapy: Applications in the Understanding of Mechanism of Action and Therapeutic Response

Debraj Guha Thakurta, Ph.D., Senior Scientist II & Group Leader, Systems Biology, Dendreon Corporation

We are using high-content platforms (DNA and protein microarrays, RNA-seq) in various stages of the development of cellular immunotherapies for cancer. We will provide examples of genomic applications that can aid in the mechanistic understanding and the discovery of molecular markers associated with the efficacy of a cancer immunotherapy..

4:15 Use of Systems Pharmacology to Aid Cancer Clinical Development

Anna Georgieva Kondic, Ph.D., MBA, Senior Principal Scientist, Modeling and Simulation, Merck Research Labs

The last few years have seen an increased use of physiologically-based pharmacokinetics and pharmacodynamics models in Oncology drug development. This is partially due to an improved mechanistic understanding of disease drivers and the collection of better patient-level quantitative data that lends itself to modeling. In this talk, a suite of studies where systems modeling was successfully used to inform either preclinical to clinical transition or clinical study design will be presented. The talk will complete with a potential systems pharmacology framework that can be used systematically in drug development.

4:45 Sponsored Presentations (Opportunities Available)

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes

 

Thursday, April 11

7:00 am Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee

 

MODELING AND MINING TARGETS

8:45 Chairperson’s Opening Remarks

8:50 Systems Biology Approach for Identification of New Targets and Biomarkers

I-Ming Wang, Ph.D., Associate Scientific Director, Research Solutions and Bioinformatics, Informatics and Analysis, Merck Research Laboratory

A representative gene signature was identified by an integrated analysis of expression data in twelve rodent inflammatory models/tissues. This “inflammatome” signature is highly enriched in known drug target genes and is significantly overlapped with macrophage-enriched metabolic networks (MEMN) reported previously. A large proportion of genes in this signature are tightly connected in several tissue-specific Bayesian networks built from multiple mouse F2 crosses and human tissue cohorts; furthermore, these tissue networks are very significantly overlapped. This indicates that variable expression in this set of co-regulated genes is the main driver of many disease states. Disease-specific gene sets with the potential of being utilized as biomarkers were also identified with the approach we applied. The identification of this “inflammatome” gene signature extends the coverage of MEMN beyond adipose and liver in the metabolic disease to multiple diseases involving various affected tissues.

9:20 Optimizing Therapeutic Index (TI) by Exploring Co-Dependencies of Target and Therapeutic Properties

Madhu Natarajan, Ph.D., Associate Director, Computational Biology, Discovery Research, Shire HGT

Conventional drug-discovery informatics workflows employ combinations of mechanistic/probabilistic in-silico methods to rank lists of targets; therapeutics are then developed for “optimal” targets. I describe a systems pharmacology approach that instead integrates systematic in-silico therapeutic perturbation with models of target/disease biology to identify conditions for optimal TI; non-intuitively optimal TI is sometimes achieved by pairing sub-optimal targets with therapeutics having appropriate properties.

9:50 Sponsored Presentations (Opportunities Available)

10:20 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

10:45 Plenary Keynote Panel Chairperson’s Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:50 Plenary Keynote Panel Introduction

Yury Rozenman, Head of BT for Life Sciences, BT Global Services

 

» PLENARY KEYNOTE PANEL

11:05 The Life Sciences CIO Panel

Panelists:
Remy Evard, CIO, Novartis Institutes for BioMedical Research
Martin Leach, Ph.D., Vice President, R&D IT, Biogen Idec
Andrea T. Norris, Director, Center for Information Technology (CIT) and Chief Information Officer, NIH
Gunaretnam Rajagopal, Ph.D., Vice President and CIO, Bioinformatics & External Innovation at Janssen Pharmaceutical Companies of Johnson & Johnson
Cris Ross, Chief Information Officer, Mayo Clinic

 

12:15 pm Luncheon in the Exhibit Hall with Poster Viewing

 

MODELING MOLECULAR AND PATHOPHYSIOLOGICAL DATA

1:55 Chairperson’s Remarks

2:00 Predicting Adverse Side Effects of Drugs Using Systems Pharmacology

Jake Chen, Ph.D., Associate Professor, Indiana University School of Informatics & Purdue University Department of Computer Science; Director, Indiana Center for Systems Biology and Personalized Medicine

A new way of studying drug toxicity is to incorporate biomolecular annotation and network data with clinical observations of drug targets upon drug perturbations. I will describe the development of a novel computational modeling framework, with which we demonstrated the highest drug toxicity prediction accuracies ever reported by far. Adoption of this framework may have profound practical drug discovery implications.

2:30 Holistic Integration of Molecular and Physiological Data and Its Application in Personalized Healthcare

David de Graaf, Ph.D. President and CEO, Selventa

There are multiple industry-wide challenges in aggregating molecular and pathophysiological data for systems pharmacology to transform the process of drug discovery and development. One of the ways to address these challenges is to utilize a common computable biological expression language (BEL) that can provide a comprehensive knowledge network for new discoveries. An application of BEL and its use in identifying clinically relevant predictive biomarkers for patient stratification will be presented.

3:00 The Role of Informatics in ADME Pharmacogenetics

Boyd SteereBoyd Steere, Ph.D., Senior Research Scientist, Lilly Research Laboraories, IT Research Informatics, Eli Lilly

The leveraging of pharmacogenetics to support decisions in early-phase clinical trial design requires informatics methods to integrate, visualize, and analyze heterogeneous data sets from many different discovery platforms.  This presentation describes challenges and solutions in making sense of diverse sets of genetic, protein, and metabolic data in support of ADME pharmacology projects.

3:30 A Systems Pharmacology Approach to Understand and Optimize Functional Selectivity for Non-Selective Drugs

Joshua Apgar, Principal Scientist, Systems Biology, Dept. of Immunology & Inflammation, Boehringer Ingelheim Pharmaceuticals, Inc.

Most commonly the selectivity of a compound is defined in an in vitro or cellular assay, and it is thought of as principally a function of the binding energy of the drug to its on-target and off-target proteins; however, in vivo functional selectivity is much more complicated, and is affected by systems level effects such as multiple feedback processes within and between the various on- and off-target pathways. These systems level processes are often impossible to reconstruct in vitro as they involve many cell types, tissues, and organs systems throughout the body. We show here that through mathematical modeling we were able to identify, in silico, molecular properties that are critical to driving functional selectivity. The models, although simple, capture the key systems pharmacology needed to understand the on- an off- target effects. Surprisingly, in this case, the key driver of functional selectivity is not the affinity of the drugs but rather the pharmacokinetics, with drugs having a short half-life predicted to be the most functionally selective.

 SOURCE:
Final Agenda

 

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Curator: Aviva Lev-Ari, PhD, RN

New Institute for Precision Medicine Created at Weill Cornell Medical College and NewYork-Presbyterian Hospital

DR. MARK RUBIN, LEADING PROSTATE CANCER AND GENOMICS EXPERT, TO LEAD CUTTING-EDGE CENTER FOR TARGETED, INDIVIDUALIZED PATIENT CARE BASED ON EACH PATIENT’S GENETICS

NEW YORK (Jan. 31, 2013) — Recognizing that medicine is not “one size fits all,” Weill Cornell Medical College and NewYork-Presbyterian Hospital have created the pioneering Institute for Precision Medicine at Weill Cornell and NewYork-Presbyterian/Weill Cornell Medical Center. This new, cutting-edge translational medicine research hub will explore the new frontier of precision medicine, offering optimal targeted, individualized treatment based on each patient’s genetic profile. The institute’s new genomic research discoveries will help develop novel, personalized medical therapies to be tested in innovative clinical trials, while also building a comprehensive biobank to improve research and patient care.

Dr. Mark Rubin

The Institute for Precision Medicine will be led by Dr. Mark Rubin, a renowned pathologist and prostate cancer expert who uses whole genomic sequencing in his laboratory to investigate DNA mutations that lead to disease, particularly prostate cancer. Dr. Rubin currently serves as vice chair for experimental pathology, director of Translational Research Laboratory Services, the Homer T. Hirst III Professor of Oncology, professor of pathology and laboratory medicine and professor of pathology in urology at Weill Cornell and is a pathologist at NewYork-Presbyterian/Weill Cornell.

Dr. Rubin and his team seek to replace the traditional one-size-fits-all medicine paradigm with one that focuses on targeted, individualized patient care using a patient’s own genetic profile and medical history. Physician-scientists at the institute will seek to precisely identify the genetic influencers of a patient’s specific illness — such as cancer, cardiovascular disease, neurodegenerative disease and others — and use this genetic information to design a more-effective course of treatment that targets those specific contributing factors. Also, genomic analyses of tumor tissue will enable researchers to help patients with advanced disease and no current treatment options, as well as to isolate the causes of drug resistance in patients who stop responding to treatments, redirecting them to more successful therapies.

Preventive precision medicine will also be a key initiative at the institute, allowing physician-scientists to help identify a patient’s risk of diseases and take necessary steps to aid in its prevention through medical treatment and/or lifestyle modification. In addition, the Institute for Precision Medicine will leverage an arsenal of innovative genomic sequencing, biobanking and bioinformatics technology to transform the existing paradigm for diagnosing and treating patients.

“This institute will revolutionize the way we treat disease, linking cutting-edge research and next-generation sequencing in the laboratory to the patient’s bedside,” Dr. Rubin says. “We will use advanced technology and the collective wealth of knowledge from our clinicians, basic scientists, pathologists, molecular biologists and computational biologists to pinpoint the molecular underpinnings of disease — information that will spur the discovery of novel treatments and therapies. It’s an exciting time to be involved in precision medicine and I look forward to advancing this game-changing field of medicine.”

“Precision medicine is the future of medicine, and its application will help countless patients,” says Dr. Laurie H. Glimcher, the Stephen and Suzanne Weiss Dean of Weill Cornell Medical College. “The Institute for Precision Medicine, with Dr. Rubin’s expertise and strong leadership, will accelerate our understanding of the human genome, provide key insights into the causes of disease and enable our physician-scientists to translate this knowledge from the lab to the clinical setting to help deliver personalized treatments to the sickest of our patients.”

Three main resources will facilitate the institute’s groundbreaking precision medicine work:

  • genomics sequencing,
  • biobanking and
  • bioinformatics.

Weill Cornell and NewYork-Presbyterian will invest in state-of-the-art technology to conduct sequencing, a more expansive biobank for all patient specimens and tissue samples and dedicated bioinformaticians who will closely analyze patient data, searching for genetic mutations and other abnormalities to identify and target with treatment.

“The Institute for Precision Medicine will enable our doctors to tailor effective treatments for individual patients and also predict the diseases that are likely to affect a patient long before they develop,” says Dr. Steven J. Corwin, CEO of NewYork-Presbyterian Hospital. “By harnessing the full potential of our enhanced understanding of the human genome, and extending its reach into the clinical realm, the institute will transform patient care at NewYork-Presbyterian/Weill Cornell Medical Center and beyond.”

Dr. Rubin, the institute’s inaugural director, is a board-certified pathologist and physician-scientist with specific expertise in genitourinary pathology and an internationally recognized leader in prostate cancer genomics and biomarker research. His groundbreaking research investigating molecular biomarkers distinguishing indolent from aggressive disease has led to landmark discoveries that revolutionized the understanding of prostate cancer’s molecular underpinnings. This includes co-discovering two of the most common mutations in prostate cancer,

  • the TMPRSS2-ETS rearrangements and 
  • SPOP mutations.

Dr. Rubin is one of the “Dream Team” principal investigators of a multi-institutional $10 million grant from Stand Up 2 Cancer (SU2C) and the Prostate Cancer Foundation, addressing patients with advanced prostate cancer through a multi-phase approach employing next generation sequencing to help inform the direction of future clinical trials. Additionally, Dr. Rubin serves as a co-principal investigator on the National Cancer Institute‘s (NCI) Early Detection Research Network (EDRN) Biomarker Discovery Laboratory and worked for many years as part of the NCI Prostate Cancer Specialized Programs of Research Excellence (SPORE).

Dr. Rubin has authored more than 275 peer-reviewed publications, predominantly in prostate cancer, and holds multiple NCI-funded grants in prostate cancer genomics and biomarker development. He is a member of the World Health Organization Prostate Cancer Tumor Classification and the Prostate TCGA (The Cancer Genome Atlas) Working Group. He serves as an ad hoc reviewer for multiple publications including Nature, Science, Cancer Cell, Cancer Discovery and the New England Journal of Medicine. Dr. Rubin also serves as the chair of the EDRN Prostate Cancer Working Group and is a member of the ERDN Steering Committee. He is active in the NCI/NHGRI-sponsored TCGA serving on the Prostate Cancer Working Group and he is an external advisor for the Canadian International Cancer Genome Consortium (ICGC). He served on the NCI Cancer Biomarker Study Section for five years and as an ad hoc reviewer for other NCI and international granting organizations.

Dr. Rubin is the recipient of the Arthur Purdy Stout Society of Surgical Pathologists Annual Prize (2003), the Young Investigator Award (2004) given by the United States and Canadian Academy of Pathology and the Huggins Medal (2012), the highest award bestowed by the Society of Urologic Oncology. Finally, Dr. Rubin was a co-team leader with his long-term collaborator, Arul M. Chinnaiyan (University of Michigan) for the first annual American Association of Cancer Research Team Science Award (2007) in recognition for their groundbreaking work on TMPRSS2-ETS fusion prostate cancer.

 SOURCE:

Clinical Laboratory Improvement Amendments (CLIA)

The Centers for Medicare & Medicaid Services (CMS) regulates all laboratory testing (except research) performed on humans in the U.S. through the Clinical Laboratory Improvement Amendments (CLIA). In total, CLIA covers approximately 225,000 laboratory entities. The Division of Laboratory Services, within the Survey and Certification Group, under the Office of Clinical Standards and Quality (OCSQ) has the responsibility for implementing the CLIA Program.

The objective of the CLIA program is to ensure quality laboratory testing. Although all clinical laboratories must be properly certified to receive Medicare or Medicaid payments, CLIA has no direct Medicare or Medicaid program responsibilities.

For the following information, refer to the downloads/links listed below:

  • For additional information about a particular laboratory, contact the appropriate State Agency or Regional Office CLIA contact (refer to State Agency or Regional Office CLIA link found on the left-hand navigation plane);
  • Information about direct access testing (DAT) and the CLIA regulations is included in the Direct Access Testing download;
  • OIG reports relating to CLIA;
  • Guidance for Coordination of CLIA Activities Among CMS Central Office, CMS Regional Offices, State Agencies (including State with Licensure Requirements), Accreditation Organizations and States with CMS Approved State Laboratory Programs is contained in the Partners in Laboratory Oversight download;
  • Quality control (QC) highlights from the regulations published in the Federal Register on January 24, 2003 are listed under the QC Highlights download;
  • Micro sample pipetting information for laboratories;
  • Information on alternative (non-traditional) laboratory is contained in the Special Alert download;
  • Identifying Best Practices in Laboratory Medicine – a Battelle Project for the Centers for Disease Control and Prevention (CDC); and
  • FDA Safety Tip for laboratories on how workload should be calculated when using currently FDA-approved semi-automated gynecologic cytology screening devices.

For specific information about the quality assurance guidelines for testing using the rapid HIV-1 antibody tests waived under CLIA, refer to the CDC Division of Laboratory Systems website listed under the related links outside CMS section below.

Complaint Reporting

To report a complaint about a laboratory, contact the appropriate State Agency that is found on the State Agency & Regional Office CLIA Contacts page located in the left navigation bar in this section.

 SOURCE:

New Weill Cornell Precision Medicine Institute Plans to Offer Genomically Guided Treatment after CLIA Approval

February 06, 2013

Through a newly created Institute for Precision Medicine,Weill Cornell Medical College and New York Presbyterian Hospital plan to begin offering targeted, individualized treatment informed by patients’ genomes.

The institute first plans to guide treatment decisions for cancer patients using their genomic data, and then broaden the effort to those with common illnesses, such as cardiovascular disease and neurodegenerative disorders.

The new institute is currently awaiting regulatory approval from CLIA and New York State, according to its leader, Mark Rubin, a professor of pathology at Weill Cornell.

With that approval in hand, the center will begin using genome sequencing and other tools to inform treatment strategies for patients – first focusing on cancer, and then eventually broadening to other disease areas, he said.

While Rubin did not detail how the institute will recruit patients, he said the center plans to see cancer patients who can benefit from single-gene tests or other molecular diagnostics to inform treatment decisions, those with advanced diseases without treatment options, and patients who stop responding to standard treatments and could be redirected to other therapies.

“For some patients, there are very clear indications of whether they need a specific targeted therapy. Those are pretty straightforward,” Rubin said.

“And then there is emerging data that sequencing, either exome or whole-genome, can provide insight on which treatments cancer patients might need that are not considered standard treatments,” he said.

Insights from advanced sequencing technologies are also changing how researchers study patients, sometimes facilitating N-of-1 trials. “There are a few examples where treatments have been implemented and shown to be effective in a clinical trial of one,” Rubin said, “where they are the only person on the trial because of their specific mutations.”

He said the institute plans to be agnostic in terms of what technologies it uses for sequencing, but currently it relies on Illumina technology.

“We will have a number of different approaches, but the key is to do as best as possible in the clinical setting so that the results can be used in the management of patients,” Rubin said.

According to Rubin, the institute aims to find the optimal ways to collect genomic data, analyze it, and store it. As the center gears up and sees larger numbers of patients, Rubin said it also plans to use data and samples it collects to support larger retrospective or prospective studies, for which the institute is considering partnering with the New York Genome Center.

But not all patients the institute sees may require large-scale genome sequencing, Rubin reiterated.

“It may turn out that the most efficient way to determine if someone has a certain mutation, like EGFR, is to run the single-gene test up front. That’s not going to change for some types of disease,” he noted. “So, what I see our role being is developing these more complex approaches, which could be whole-genome sequencing, or using multiplex panels of genes.”

The institute will focus its efforts first on cancer patients because the development of genomically targeted therapies is relatively accelerated compared to other disease areas, so the potential to match a mutation in a cancer patient’s genome to a potential treatment may be greater than for those with other illnesses. But according to Rubin, the institute does plan to expand to other populations, like cardiovascular conditions, neurodegenerative diseases, and possibly infectious diseases.

In addition, he said the Institute is also discussing how it might use prognostic genomic information to look at disease risk, with the potential to inform early interventional treatment decision making.

“Because we are a hospital that sees well patients being followed by their doctors, that’s something we’re contemplating as pilot,” he said.

“We don’t have a plan in mind yet, but those types of studies are probably very important in specific disease entities, for patients at risk for a particular constitutional disease … or you could imagine we might screen large numbers of our patient population to look for risk factors that may not have been identified yet,” he said.

Several commercial and academic groups have recently begun offering clinical cancer sequencing and other genomic analyses to potentially guide therapeutic decision making.

Foundation Medicine, for example, sells a test that sequences the exons of nearly 200 genes known to be mutated in solid tumors and provides a report informing doctors of actionable mutations.

Other firms, like Caris Life Sciences, provide reports to doctors and patients matching gene-expression or sequence data to potentially actionable therapies.

The University of Michigan and the International Genomics Consortium announced last fall that they were creating a non-profit company called Paradigm to provide a targeted-sequencing-based diagnostic service to guide personalized treatment for cancer and, eventually, other diseases (PGx Reporter 7/5/2012).

Though the new Weill Cornell institute plans to start fairly narrowly, Rubin’s overall goals for the center may put it in a position to offer a potentially more comprehensive service than many of these other groups.

“The most challenging part right now is for us to understand that sequencing is just a test, something that may or may not be useful in itself. It’s in working in the clinical setting that we are going to really define it,” Rubin said.

The institute, in the early days of its operations, is still in a learning phase, but “expectations are high” for the effort to succeed, according to Rubin. “Our job is to live up to the promise [of sequencing] to help identify novel targets for patients who may not have any choices with respect to treatment,” Rubin said. “And also to make discoveries that may be useful for a larger population.”

Molika Ashford is a GenomeWeb contributing editor and covers personalized medicine and molecular diagnostics. E-mail Molika Ashford.

Related Stories

SOURCE:

Complaint Reporting

To report a complaint about a laboratory, contact the appropriate State Agency that is found on the State Agency & Regional Office CLIA Contacts page located in the left navigation bar in this section.

Read Full Post »

Reporter: Ritu Saxena, Ph.D.

With the number of cancer cases plummeting every year, there is a dire need for finding a cure to wipe the disease out. A number of therapeutic drugs are currently in use, however, due to heterogeneity of the disease targeted therapy is required. An important criteria that needs to be addressed in this context is the –‘tumor response’ and how it could be predicted, thereby improving the selection of patients for cancer treatment. The issue of tumor response has been addressed in a recent editorial titled “Tumor response criteria: are they appropriate?” published recently in Future Oncology.

The article talks about how the early tumor treatment response methods came into practice and how we need to redefine and reassess the tumor response.

Defining ‘tumor response’ has always been a challenge

WHO defines a response to anticancer therapy as 50% or more reduction in the tumor size measured in two perpendicular diameters. It is based on the results of experiments performed by Moertel and Hanley in 1976 and later published by Miller et al in 1981. Twenty years later, in the year 2000, the US National Cancer Institute, with the European Association for Research and Treatment of Cancer, proposed ‘new response criteria’ for solid tumors; a replacement of 2D measurement with measurement of one dimen­sion was made. Tumor response was defined as a decrease in the largest tumor diameter by 30%, which would translate into a 50% decrease for a spherical lesion. However, response criteria have not been updated after that and there a structured standardization of treatment response is still required especially when several studies have revealed that the response of tumors to a therapy via imaging results from conventional approaches such as endoscopy, CT scan, is not reliable. The reason is that evaluating the size of tumor is just one part of the story and to get the complete picture inves­tigating and evaluating the tissue is essential to differentiate between treatment-related scar, fibrosis or micro­scopic residual tumor.

In clinical practice, treatment response is determined on the basis of well-established parameters obtained from diagnostic imaging, both cross-sectional and functional. In general, the response is classified as:

  • Complete remission: If a tumor disappears after a particular therapy,
  • Partial remission: there is residual tumor after therapy.

For a doctor examining the morphology of the tumor, complete remission might seem like good news, however, mission might not be complete yet! For example, in some cases, with regard to prognosis, patients with 0% residual tumor (complete tumor response) had the same prognosis com­pared with those patients with 1–10% residual tumor (subtotal response).

Another example is that in patients demonstrating complete remission of tumor response as observed with clinical, sonographic, functional (PET) and histopathological analysis experience recur­rence within the first 2 years of resection.

Adding complexity to the situation is the fact that the appropriate, clinically relevant timing of assess­ment of tumor response to treatment remains undefined. An example mentioned in the editorial is – for gastrointestinal (GI) malignancies, the assessment timing varies considerably from 3 to 6 weeks after initia­tion of neoadjuvant external beam radiation. Further, time could vary depending upon the type of radiation administered, i.e., if it is external beam, accelerated hyperfractionation, or brachytherapy.

Abovementioned examples remind us of the intricacy and enigma of tumor biol­ogy and subsequent tumor response.

Conclusion

Owing to the extraordinary het­erogeneity of cancers between patients, and pri­mary and metastatic tumors in the same patients, it is important to consider several factors while determining the response of tumors to different therapie in clinical trials. Authors exclaim, “We must change the tools we use to assess tumor response. The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ charac­teristics.”

Future perspective

Editorial points out that the oncologists, radiotherapists, and immunologists all might have a different opinion and observation as far as tumor response is considered. For example, surgical oncologists might determine a treatment to be effective if the local tumor control is much better after multimodal treatment, and that patients post-therapeutically also reveal an increase of the rate of microscopic and macroscopic R0-resection. Immunologists, on the other hand, might just declare a response if immune-competent cells have been decreased and, possibly, without clinical signs of decrease of tumor size.

What might be the answer to the complexity to reading tumor response is stated in the editorial – “an interdisciplinary initiative with all key stake­holders and disciplines represented is imperative to make predictive and prognostic individualized tumor response assessment a modern-day reality. The integrated multidisciplinary panel of international experts need to define how to leverage existing data, tissue and testing platforms in order to predict individual patient treatment response and prog­nosis.”

Sources:

Editorial : Björn LDM Brücher et al Tumor response criteria: are they appropriate? Future Oncology August 2012, Vol. 8, No. 8, 903-906.

Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer 1981, 47(1),207–214.

Related articles to this subject on this Open Access Online Scientific Journal:

See comment written for :

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying

http://pharmaceuticalintelligence.com/2012/10/16/knowing-the-tumors-size-and-location-could-we-target-treatment-to-the-roi-by-applying-imaging-guided-intervention/imaging-guided intervention?

Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

http://pharmaceuticalintelligence.com/2012/12/01/personalized-medicine-cancer-cell-biology-and-minimally-invasive-surgery-mis/

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Author: Tilda Barliya PhD

In response to the previous post:

Paclitaxel vs Abraxane (albumin-bound paclitaxel)

http://pharmaceuticalintelligence.com/2012/11/17/paclitaxel-vs-abraxane-albumin-bound-paclitaxel/

Pharmacogenomics properties are presented, below.

Paclitaxel is a mitotic inhibitor used in cancer chemotherapy. It was discovered in a U.S. National Cancer Institute program at the Research Triangle Institute (North Carolina)  in 1967 when Monroe E.Wall and Mansukh C.Wani  isolated it from the bark of the Pacific yew tree, Taxus brevifolia and named it taxol. Later it was discovered that endophytic fungi in the bark synthesize paclitaxel.

Paclitaxel is currently being indicated to lung, breast and ovarian cancer as well as  head and neck cancer, and advanced forms of Kaposi’s sarcoma. 

The administration of paclitaxel (Taxol®) through intravenous infusions was achieved by using Cremophor® EL as a vehicle to entrap the drug in micelles and keep it in solution, which affects the disposition of paclitaxel and is responsible for the nonlinear pharmacokinetics of the drug, especially at higher dose levels. (http://www.futuremedicine.com/doi/pdf/10.2217/pgs.10.32)

Although Nonlinear pharmacokinetics (dose-dependented kinetics) may occur in all aspects of pharmacokinetics (absorption, distribution, and/or elimination), it focus on the in the metabolism or MichaelisMenten (MM) kinetics of the drug. http://archive.ajpe.org/legacy/pdfs/aj650212.pdf

Briefly, it is known that some of these adverse effects such as hypersensitivity reactions were diminished with the administration of corticosteroids and H1 and H2 antihistamine premedication, and by reducing the incidence of grade 3/4 neutropenia with the administration of granulocyte colony-stimulating factors (G-CSF) and shortening paclitaxel infusion time from 24 to 3 h. However, the neurotoxicity, which was believed to be caused by either paclitaxel or Cremophor EL, could not be controlled and became the dose-limiting toxicity of the drug. It was later on found that paclitaxel itself was responsible to the neurotoxicity effects (http://annonc.oxfordjournals.org/content/6/7/699.abstract)

Pharmacokinetics and Pharmacodynamics

The selection of pharmacokinetic (PK) parameter end points and basic model types for exposure-toxicity relationships of paclitaxel is usually based on tradition rather than physiological relevance.

pharmacokinetic (PK)-pharmacodynamic (PD) relationships for paclitaxel are still most commonly described with empirically-designed threshold models, which have little or no mechanistic basis and lack usefulness when applied to conditions (eg, schedules, vehicles, or routes of administration) different from those from which they were originally derived. (http://jco.ascopubs.org/content/21/14/2803.long). As such, the AUC of the unbound paclitaxel is highly important as a pharmacokinetic parameter to describe exposure-neutropenia relationships (the unbound ptx was not evaluated yet). (http://clincancerres.aacrjournals.org.rproxy.tau.ac.il/content/1/6/599.full.pdf+html)

The clearance of Cremophor EL in patients was found to be time-dependent, resulting in disproportional increases in systemic exposure being associated with shortening of infusion from 3 hours to 1 hour.

One study (http://clincancerres.aacrjournals.org/content/1/6/599), compare the pharmacokinetics and pharmacodynamics (PD) of paclitaxel between Phase I trials of 3- and 24-h infusions and to determine the most informative pharmacokinetic parameter to describe the PD. The study had 3 main goals

  • (a) to compare the PK and PD of paclitaxel between Phase I studies of 3- and 24-h infusion,
  • (b) to examine the relationship between PK and PD
  • (c) to determine the most informative pharmacokinetic parameter to describe the PD.

Note: Although this study was conducted in ~1993-1995, is has been cited extensively and paved the was to other clinical trials with similar results.

27 patients were treated in a Phase I study of paclitaxel by a 3-h infusion at one of six doses: 105, 135, 180, 210, 240, and 270 mg/m2. Pharmacokinetic data were obtained from all patients. Paclitaxel concentrations were measured in the plasma and urine using HPLC. Similar eligibility criteria were designed for the 24-hr infusion with these doses were 49.5, 75, 105, 135, and 180 mg/m2 . Plasma and urine samples for pharmacokinetic evaluation of paclitaxel were collected.

Pharmacokinetic Analysis: Pharmacokinetic parameters, Cmax, AUC, t112, and MRT were obtained by a noncompartmental moment method. Cmax was actually observed peak concentration. AUC and MRT were computed by trapezoidal integration with extrapolation to infinite time.

Pharmacodynamic Analysis: The pharmacokinetic/pharmacodynamic relationships were modeled with the sigmoid maximum effect

Results:

Pharmacokinetic analysis:

The drug plasma concentration increased throughout the 3-h infusion period and began to decrease immediately upon cessation of the infusion with t112 of 9.9-16.0 h and MRT of 6.47-10.24 h (Fig. 1). Both Cmax and AUC increased with increasing doses (r = 0.865, P <0.001 for Cmax r 0.870, P < 0.001 for AUC), although the pharmacokinetic behavior appeared to be nonlinear (Fig. 2). The mean Cmax and AUC at a dose of 270 mg/m2 were more than 3-fold greater than those at a dose of 135 mg/m2. CL and V, decreased with increasing doses (Table 1). The urinary excretion of paclitaxel over 75 h was less than 15% of the dose administered, which indicated that non-renal excretion is the primary route of drug elimination.

The urinary excretion of paclitaxel over 75 h was less than 15% of the dose administered, which indicated that non-renal excretion is the primary route of drug elimination.

Comparison of PD between 3-h and 24-h Infusion

Groups. AUC and duration of plasma concentration (h) above (7>) 0.05-0.1 LM correlated with the % D in granulocytes with p values less than 0.05. The best parameter predicting granulocytopenia was T> 0.09 pM with the minimum of the Akaike Information Criterion. In the 24-h schedule, dose, AUC, and T > 0.04-0.07 pM were demonstrated to correlate with the % D in granulocytes. The best parameter predicting granulocytopenia in the 24-h schedule was T > 0.05 p.M.

Nonhematological toxicities such as peripheral neuropathy, hypotension, and arthralgialmyalgia mainly observed in the 3-h infusion group had no relationship with Cm or AUC which are much higher in the 3-h infusion group, although peripheral neuropathy and musculoskeletal toxicity have been suggested to be associated with AUC on a 6- (12) or 24-h (29) schedule.

Pharmacogenomics:

In the past, the major adverse effects encountered with Taxol were severe hypersensitivity reactions, mainly attributed to Cremophor EL; hematologic toxicity, primarily appearing in the form of severe neutropenia; and neurotoxicity, mainly seen as cumulative sensory peripheral neuropathy. The mechanism for the neurotoxicity has been demonstrated to involve ganglioneuropathy and axonopathy caused by dysfunctional microtubules in dorsal root ganglia, axons and Schwann cells.

Variability in paclitaxel pharmacokinetics has  been associated with the adverse effects of the  drug. Thus, polymorphisms in genes encoding  paclitaxel-metabolizing enzymes, transporters and therapeutic targets have been suggested  to contribute to the interindividual variability in toxicity and response.

Further characterization of  genes involved in paclitaxel elimination and drug  response was performed, including the identification of their most relevant genetic variants. The organic anion transporting polypeptide (OATP)  1B3 was identified as a key protein for paclitaxel hepatic uptake and polymorphisms in the genes encoding for paclitaxel metabolizing enzymes and transporters (CYP2C8, CYP3A4) CYP3A5, P-glycoprotein and OATP1B3) (http://www.futuremedicine.com/doi/pdf/10.2217/pgs.10.32)

***It is important to note that  the allele frequencies for many of these polymorphisms are subject to important ethnicity  specific differences, with some alleles exclusively present in specific populations (e.g., the Caucasian CYP2C8*3).

For the CYP2C8 gene, two alleles common in Caucasians that result in amino acid changes CYP2C8*3 (R139K; K399R) and CYP2C8*4 (I264M), were described. The former has been shown to possess an altered activity, while the latter does not seem to have functional
consequences. In addition, two CYP2C8 haplotypes were recently shown to confer an increased and reduced metabolizing activity, respectively.

CYP3A5 was found to be highly polymorphic owing to CYP3A5*3, CYP3A5*6 and CYP3A5*7 , with the latter two being African-specific polymorphisms.

Pharmacogenetic studies comparing the most relevant polymorphisms in these genes and paclitaxel pharmacokinetics have rendered contradictory results, with some studies finding no associations while others reported an effect for ABCB1, CYP3A4 or CYP2C8 polymorphisms on specific pharmacokinetic parameters.

Again, with respect to paclitaxel neurotoxicity risk, some studies have rendered positive results for ABCB1 , CYP2C8  and CYP3A5  polymorphisms, while others found no significant associations.

Note: These differences might be caused by underpowered studies and by differences in the patients under study.

Changes affecting microtubule  structure and/or composition have been shown to affect paclitaxel efficacy, probably by reducing drug–target affinity. Mainly, resistance to tubulin-binding agents has been associated with an overexpression of b-tubulin isotype III,
which seems to be caused by a deregulation of the microRNA family 200.

However, the clinical utility of these findings remains to be established; furthermore, the identification of biomarkers that could be used to individualize paclitaxel treatment remains a challenge.

In summary,

  1. Pharmacokinetics: Paclitaxel seems to have a non-linear (=dose-dependent) PK parameters.
  2. Pharmcokinetics- Pharmacodynamics: Previous clinical trials did NOT take into account the unbound concentrations of Ptx and therefore in the PK analysis, therefore newly designed clinical trials should take that into consideration. This is very important since the neurotoxicity is attributed to ptx and not its vehicle Cremophor (as shown in the PD analysis)
  3. Difficult to compare between the 3hr and 24hr infusion schedule as most clinical trials did NOT used similar dose-regime making the comparison very hard.
  4. Pharmacogenetics: Different polymorphisms seems to attribute to the been suggested  to contribute to the interindividual variability in toxicity and response.
  5. Prospective pharmacogenetic-guided clinical trials will be required in order to accurately establish the utility of the identified markers/strategies for patients and healthcare systems.

 

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