Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com
Bacterial multidrug resistance problem solved by a broad-spectrum synthetic antibiotic
Reporter and Curator: Dr. Sudipta Saha, Ph.D.
There is an increasing demand for new antibiotics that effectively treat patients with refractory bacteremia, do not evoke bacterial resistance, and can be readily modified to address current and anticipated patient needs. Recently scientists described a promising compound of COE (conjugated oligo electrolytes) family, COE2-2hexyl, that exhibited broad-spectrum antibacterial activity. COE2-2hexyl effectively-treated mice infected with bacteria derived from sepsis patients with refractory bacteremia, including a CRE K. pneumoniae strain resistant to nearly all clinical antibiotics tested. Notably, this lead compound did not evoke drug resistance in several pathogens tested. COE2-2hexyl has specific effects on multiple membrane-associated functions (e.g., septation, motility, ATP synthesis, respiration, membrane permeability to small molecules) that may act together to abrogate bacterial cell viability and the evolution of drug-resistance. Impeding these bacterial properties may occur through alteration of vital protein–protein or protein-lipid membrane interfaces – a mechanism of action distinct from many membrane disrupting antimicrobials or detergents that destabilize membranes to induce bacterial cell lysis. The diversity and ease of COE design and chemical synthesis have the potential to establish a new standard for drug design and personalized antibiotic treatment.
Recent studies have shown that small molecules can preferentially target bacterial membranes due to significant differences in lipid composition, presence of a cell wall, and the absence of cholesterol. The inner membranes of Gram-negative bacteria are generally more negatively charged at their surface because they contain more anionic lipids such as cardiolipin and phosphatidylglycerol within their outer leaflet compared to mammalian membranes. In contrast, membranes of mammalian cells are largely composed of more-neutral phospholipids, sphingomyelins, as well as cholesterol, which affords membrane rigidity and ability to withstand mechanical stresses; and may stabilize the membrane against structural damage to membrane-disrupting agents such as COEs. Consistent with these studies, COE2-2hexyl was well tolerated in mice, suggesting that COEs are not intrinsically toxic in vivo, which is often a primary concern with membrane-targeting antibiotics. The COE refinement workflow potentially accelerates lead compound optimization by more rapid screening of novel compounds for the iterative directed-design process. It also reduces the time and cost of subsequent biophysical characterization, medicinal chemistry and bioassays, ultimately facilitating the discovery of novel compounds with improved pharmacological properties.
Additionally, COEs provide an approach to gain new insights into microbial physiology, including membrane structure/function and mechanism of drug action/resistance, while also generating a suite of tools that enable the modulation of bacterial and mammalian membranes for scientific or manufacturing uses. Notably, further COE safety and efficacy studies are required to be conducted on a larger scale to ensure adequate understanding of the clinical benefits and risks to assure clinical efficacy and toxicity before COEs can be added to the therapeutic armamentarium. Despite these limitations, the ease of molecular design, synthesis and modular nature of COEs offer many advantages over conventional antimicrobials, making synthesis simple, scalable and affordable. It enables the construction of a spectrum of compounds with the potential for development as a new versatile therapy for the emergence and rapid global spread of pathogens that are resistant to all, or nearly all, existing antimicrobial medicines.
2021 Virtual World Medical Innovation Forum, Mass General Brigham, Gene and Cell Therapy, VIRTUAL May 19–21, 2021
The 2021 Virtual World Medical Innovation Forum will focus on the growing impact of gene and cell therapy. Senior healthcare leaders from all over look to shape and debate the area of gene and cell therapy. Our shared belief: no matter the magnitude of change, responsible healthcare is centered on a shared commitment to collaborative innovation–industry, academia, and practitioners working together to improve patients’ lives.
About the World Medical Innovation Forum
Mass General Brigham is pleased to present the World Medical Innovation Forum (WMIF) virtual event Wednesday, May 19 – Friday, May 21. This interactive web event features expert discussions of gene and cell therapy (GCT) and its potential to change the future of medicine through its disease-treating and potentially curative properties. The agenda features 150+ executive speakers from the healthcare industry, venture, startups, life sciences manufacturing, consumer health and the front lines of care, including many Harvard Medical School-affiliated researchers and clinicians. The annual in-person Forum will resume live in Boston in 2022. The World Medical Innovation Forum is presented by Mass General Brigham Innovation, the global business development unit supporting the research requirements of 7,200 Harvard Medical School faculty and research hospitals including Massachusetts General, Brigham and Women’s, Massachusetts Eye and Ear, Spaulding Rehab and McLean Hospital. Follow us on Twitter: twitter.com/@MGBInnovation
Accelerating the Future of Medicine with Gene and Cell Therapy What Comes Next
Co-Chairs identify the key themes of the Forum – set the stage for top GCT opportunities, challenges, and where the field might take medicine in the future. Moderator: Susan Hockfield, PhD
President Emerita and Professor of Neuroscience, MIT
Hope that CGT emerging, how the therapies work, neuro, muscular, ocular, genetic diseases of liver and of heart revolution for the industry 900 IND application 25 approvals Economic driver Skilled works, VC disease. Modality one time intervention, long duration of impart, reimbursement, ecosystem to be built around CGT
FDA works by indications and risks involved, Standards and expectations for streamlining manufacturing, understanding of process and products
payments over time payers and Innovators relations Moderator: Julian Harris, MD
Partner, Deerfield
Promise of CGT realized, what part?
FDA role and interaction in CGT
Manufacturing aspects which is critical Speaker: Dave Lennon, PhD
President, Novartis Gene Therapies
Hope that CGT emerging, how the therapies work, neuro, muscular, ocular, genetic diseases of liver and of heart revolution for the industry 900 IND application 25 approvals Economic driver Skilled works, VC disease. Modality one time intervention, long duration of impart, reimbursement, ecosystem to be built around CGT
FDA works by indications and risks involved, Standards and expectations for streamlining manufacturing, understanding of process and products
payments over time payers and Innovators relations
GCT development for rare diseases is driven by patient and patient-advocate communities. Understanding their needs and perspectives enables biomarker research, the development of value-driving clinical trial endpoints and successful clinical trials. Industry works with patient communities that help identify unmet needs and collaborate with researchers to conduct disease natural history studies that inform the development of biomarkers and trial endpoints. This panel includes patients who have received cutting-edge GCT therapy as well as caregivers and patient advocates. Moderator: Patricia Musolino, MD, PhD
Co-Director Pediatric Stroke and Cerebrovascular Program, MGH
Assistant Professor of Neurology, HMS
What is the Power of One – the impact that a patient can have on their own destiny by participating in Clinical Trials Contacting other participants in same trial can be beneficial Speakers: Jack Hogan
Parkinson patient Constraints by regulatory on participation in clinical trial advance stage is approved participation Patients to determine the level of risk they wish to take Information dissemination is critical Barbara Lavery
Chief Program Officer, ACGT Foundation
Advocacy agency beginning of work Global Genes educational content and out reach to access the information
Patient has the knowledge of the symptoms and recording all input needed for diagnosis by multiple clinicians Early application for CGTDan Tesler
Clinical Trial Patient, BWH/DFCC
Experimental Drug clinical trial patient participation in clinical trial is very important to advance the state of scienceSarah Beth Thomas, RN
Professional Development Manager, BWH
Outcome is unknown, hope for good, support with resources all advocacy groups,
Process at FDA generalize from 1st entry to rules more generalizable Speaker: Peter Marks, MD, PhD
Director, Center for Biologics Evaluation and Research, FDA
Last Spring it became clear that something will work a vaccine by June 2020 belief that enough candidates the challenge manufacture enough and scaling up FDA did not predicted the efficacy of mRNA vaccine vs other approaches expected to work
Recover Work load for the pandemic will wean & clear, Gene Therapies IND application remained flat in the face of the pandemic Rare diseases urgency remains Consensus with industry advisory to get input gene therapy Guidance T-Cell therapy vs Regulation best thinking CGT evolve speedily flexible gained by Guidance
Immune modulators, Immunotherapy Genome editing can make use of viral vectors future technologies nanoparticles and liposome encapsulation
big pharma has portfolios of therapeutics not one drug across Tx areas: cell, gene iodine therapy
collective learning infrastructure features manufacturing at scale early in development Acquisitions strategy for growth # applications for scaling Rick Modi
CEO, Affinia Therapeutics
Copy, paste EDIT from product A to B novel vectors leverage knowledge varient of vector, coder optimization choice of indication is critical exploration on larger populations Speed to R&D and Speed to better gene construct get to clinic with better design vs ASAP
Data sharing clinical experience with vectors strategies patients selection, vector selection, mitigation, patient type specific Louise Rodino-Klapac, PhD
AAV based platform 15 years in development same disease indication vs more than one indication stereotype, analytics as hurdle 1st was 10 years 2nd was 3 years
Safety to clinic vs speed to clinic, difference of vectors to trust
Recent AAV gene therapy product approvals have catalyzed the field. This new class of therapies has shown the potential to bring transformative benefit to patients. With dozens of AAV treatments in clinical studies, all eyes are on the field to gauge its disruptive impact.
The panel assesses the largest challenges of the first two products, the lessons learned for the broader CGT field, and the extent to which they serve as a precedent to broaden the AAV modality.
Is AAV gene therapy restricted to genetically defined disorders, or will it be able to address common diseases in the near term?
Lessons learned from these first-in-class approvals.
Challenges to broaden this modality to similar indications.
Reflections on safety signals in the clinical studies?
Tissue types additional administrations, tech and science, address additional diseases, more science for photoreceptors a different tissue type underlying pathology novelties in last 10 years
Laxterna success to be replicated platform, paradigms measurement visual improved
More science is needed to continue develop vectors reduce toxicity,
AAV can deliver different cargos reduce adverse events improve vectorsRon Philip
Chief Operating Officer, Spark Therapeutics
The first retinal gene therapy, voretigene neparvovec-rzyl (Luxturna, Spark Therapeutics), was approved by the FDA in 2017.Meredith Schultz, MD
Executive Medical Director, Lead TME, Novartis Gene Therapies
Impact of cell therapy beyond muscular dystrophy, translational medicine, each indication, each disease, each group of patients build platform unlock the promise
Monitoring for Safety signals real world evidence remote markers, home visits, clinical trial made safer, better communication of information
AAV a complex driver in Pharmacology durable, vector of choice, administer in vitro, gene editing tissue specificity, pharmacokinetics side effects and adverse events manufacturability site variation diversify portfolios,
This panel will address the advances in the area of AAV gene therapy delivery looking out the next five years. Questions that loom large are: How can biodistribution of AAV be improved? What solutions are in the wings to address immunogenicity of AAV? Will patients be able to receive systemic redosing of AAV-based gene therapies in the future? What technical advances are there for payload size? Will the cost of manufacturing ever become affordable for ultra-rare conditions? Will non-viral delivery completely supplant viral delivery within the next five years?What are the safety concerns and how will they be addressed? Moderators: Xandra Breakefield, PhD
Ataxia requires therapy targeting multiple organ with one therapy, brain, spinal cord, heart several IND, clinical trials in 2022Mathew Pletcher, PhD
SVP, Head of Gene Therapy Research and Technical Operations, Astellas
Work with diseases poorly understood, collaborations needs example of existing: DMD is a great example explain dystrophin share placedo data
Continue to explore large animal guinea pig not the mice, not primates (ethical issues) for understanding immunogenicity and immune response Manny Simons, PhD
CEO, Akouos
AAV Therapy for the fluid of the inner ear, CGT for the ear vector accessible to surgeons translational work on the inner ear for gene therapy right animal model
Biology across species nerve ending in the cochlea
engineer out of the caspid, lowest dose possible, get desired effect by vector use, 2022 new milestones
The GCT M&A market is booming – many large pharmas have made at least one significant acquisition. How should we view the current GCT M&A market? What is its impact of the current M&A market on technology development? Are these M&A trends new are just another cycle? Has pharma strategy shifted and, if so, what does it mean for GCT companies? What does it mean for patients? What are the long-term prospects – can valuations hold up? Moderator: Adam Koppel, MD, PhD
Managing Director, Bain Capital Life Sciences
What acquirers are looking for??
What is the next generation vs what is real where is the industry going? Speakers:
Debby Baron,
Worldwide Business Development, Pfizer
CGT is an important area Pfizer is active looking for innovators, advancing forward programs of innovation with the experience Pfizer has internally
Scalability and manufacturing regulatory conversations, clinical programs safety in parallel to planning getting drug to patients
ALS – Man 1in 300, Women 1 in 400, next decade increase 7%
10% ALS is heredity 160 pharma in ALS space, diagnosis is late 1/3 of people are not diagnosed, active community for clinical trials Challenges: disease heterogeneity cases of 10 years late in diagnosis. Clinical Trials for ALS in Gene Therapy targeting ASO1 protein therapies FUS gene struck youngsters
Cell therapy for ACTA2 Vasculopathy in the brain and control the BP and stroke – smooth muscle intima proliferation. Viral vector deliver aiming to change platform to non-viral delivery rare disease , gene editing, other mutations of ACTA2 gene target other pathway for atherosclerosis
Oncolytic viruses represent a powerful new technology, but so far an FDA-approved oncolytic (Imlygic) has only occurred in one area – melanoma and that what is in 2015. This panel involves some of the protagonists of this early success story. They will explore why and how Imlygic became approved and its path to commercialization. Yet, no other cancer indications exist for Imlygic, unlike the expansion of FDA-approved indication for immune checkpoint inhibitors to multiple cancers. Why? Is there a limitation to what and which cancers can target? Is the mode of administration a problem?
No other oncolytic virus therapy has been approved since 2015. Where will the next success story come from and why? Will these therapies only be beneficial for skin cancers or other easily accessible cancers based on intratumoral delivery?
The panel will examine whether the preclinical models that have been developed for other cancer treatment modalities will be useful for oncolytic viruses. It will also assess the extent pre-clinical development challenges have slowed the development of OVs. Moderator: Nino Chiocca, MD, PhD
Neurosurgeon-in-Chief and Chairman, Neurosurgery, BWH
Harvey W. Cushing Professor of Neurosurgery, HMS
Challenges of manufacturing at Amgen what are they? Speakers: Robert Coffin, PhD
Chief Research & Development Officer, Replimune
2002 in UK promise in oncolytic therapy GNCSF
Phase III melanoma 2015 M&A with Amgen
oncolytic therapy remains non effecting on immune response
data is key for commercialization
do not belief in systemic therapy achieve maximum immune response possible from a tumor by localized injection Roger Perlmutter, MD, PhD
Chairman, Merck & Co.
response rates systemic therapy like PD1, Keytruda, OPTIVA well tolerated combination of Oncolytic with systemic
Physician, Dana Farber-Brigham and Women’s Cancer Center
Assistant Professor of Medicine, HMS
Which person gets oncolytics virus if patient has immune suppression due to other indications
Safety of oncolytic virus greater than Systemic treatment
series biopsies for injected and non injected tissue and compare Suspect of hot tumor and cold tumors likely to have sme response to agent unknown all potential
There are currently two oncolytic virus products on the market, one in the USA and one in China. As of late 2020, there were 86 clinical trials 60 of which were in phase I with just 2 in Phase III the rest in Phase I/II or Phase II. Although global sales of OVs are still in the ramp-up phase, some projections forecast OVs will be a $700 million market by 2026. This panel will address some of the major questions in this area:
What regulatory challenges will keep OVs from realizing their potential? Despite the promise of OVs for treating cancer only one has been approved in the US. Why has this been the case? Reasons such have viral tropism, viral species selection and delivery challenges have all been cited. However, these are also true of other modalities. Why then have oncolytic virus approaches not advanced faster and what are the primary challenges to be overcome?
Will these need to be combined with other agents to realize their full efficacy and how will that impact the market?
Why are these companies pursuing OVs while several others are taking a pass?
In 2020 there were a total of 60 phase I trials for Oncolytic Viruses. There are now dozens of companies pursuing some aspect of OV technology. This panel will address:
How are small companies equipped to address the challenges of developing OV therapies better than large pharma or biotech?
Will the success of COVID vaccines based on Adenovirus help the regulatory environment for small companies developing OV products in Europe and the USA?
Is there a place for non-viral delivery and other immunotherapy companies to engage in the OV space? Would they bring any real advantages?
Systemic delivery Oncolytic Virus IV delivery woman in remission
Collaboration with Regeneron
Data collection: Imageable reporter secretable reporter, gene expression
Field is intense systemic oncolytic delivery is exciting in mice and in human, response rates are encouraging combination immune stimulant, check inhibitors
Few areas of potential cancer therapy have had the attention and excitement of CAR-T. This panel of leading executives, developers, and clinician-scientists will explore the current state of CAR-T and its future prospects. Among the questions to be addressed are:
Is CAR-T still an industry priority – i.e. are new investments being made by large companies? Are new companies being financed? What are the trends?
What have we learned from first-generation products, what can we expect from CAR-T going forward in novel targets, combinations, armored CAR’s and allogeneic treatment adoption?
Early trials showed remarkable overall survival and progression-free survival. What has been observed regarding how enduring these responses are?
Most of the approvals to date have targeted CD19, and most recently BCMA. What are the most common forms of relapses that have been observed?
Is there a consensus about what comes after these CD19 and BCMA trials as to additional targets in liquid tumors? How have dual-targeted approaches fared?
The potential application of CAR-T in solid tumors will be a game-changer if it occurs. The panel explores the prospects of solid tumor success and what the barriers have been. Questions include:
How would industry and investor strategy for CAR-T and solid tumors be characterized? Has it changed in the last couple of years?
Does the lack of tumor antigen specificity in solid tumors mean that lessons from liquid tumor CAR-T constructs will not translate well and we have to start over?
Whether due to antigen heterogeneity, a hostile tumor micro-environment, or other factors are some specific solid tumors more attractive opportunities than others for CAR-T therapy development?
Given the many challenges that CAR-T faces in solid tumors, does the use of combination therapies from the start, for example, to mitigate TME effects, offer a more compelling opportunity.
Executive Director, Head of Cell Therapy Research, Exploratory Immuno-Oncology, NIBR
2017 CAR-T first approval
M&A and research collaborations
TCR tumor specific antigens avoid tissue toxicity Knut Niss, PhD
CTO, Mustang Bio
tumor hot start in 12 month clinical trial solid tumors , theraties not ready yet. Combination therapy will be an experimental treatment long journey checkpoint inhibitors to be used in combination maintenance Lipid tumor Barbra Sasu, PhD
CSO, Allogene
T cell response at prostate cancer
tumor specific
cytokine tumor specific signals move from solid to metastatic cell type for easier infiltration
Where we might go: safety autologous and allogeneic Jay Short, PhD
Chairman, CEO, Cofounder, BioAlta, Inc.
Tumor type is not enough for development of therapeutics other organs are involved in the periphery
difficult to penetrate solid tumors biologics activated in the tumor only, positive changes surrounding all charges, water molecules inside the tissue acidic environment target the cells inside the tumor and not outside
The modes of GCT manufacturing have the potential of fundamentally reordering long-established roles and pathways. While complexity goes up the distance from discovery to deployment shrinks. With the likelihood of a total market for cell therapies to be over $48 billion by 2027, groups of products are emerging. Stem cell therapies are projected to be $28 billion by 2027 and non-stem cell therapies such as CAR-T are projected be $20 billion by 2027. The manufacturing challenges for these two large buckets are very different. Within the CAR-T realm there are diverging trends of autologous and allogeneic therapies and the demands on manufacturing infrastructure are very different. Questions for the panelists are:
Help us all understand the different manufacturing challenges for cell therapies. What are the trade-offs among storage cost, batch size, line changes in terms of production cost and what is the current state of scaling naïve and stem cell therapy treatment vs engineered cell therapies?
For cell and gene therapy what is the cost of Quality Assurance/Quality Control vs. production and how do you think this will trend over time based on your perspective on learning curves today?
Will point of care production become a reality? How will that change product development strategy for pharma and venture investors? What would be the regulatory implications for such products?
How close are allogeneic CAR-T cell therapies? If successful what are the market implications of allogenic CAR-T? What are the cost implications and rewards for developing allogeneic cell therapy treatments?
Global Head of Product Development, Gene & Cell Therapy, Catalent
2/3 autologous 1/3 allogeneic CAR-T high doses and high populations scale up is not done today quality maintain required the timing logistics issues centralized vs decentralized allogeneic are health donors innovations in cell types in use improvements in manufacturing
China embraced gene and cell therapies early. The first China gene therapy clinical trial was in 1991. China approved the world’s first gene therapy product in 2003—Gendicine—an oncolytic adenovirus for the treatment of advanced head and neck cancer. Driven by broad national strategy, China has become a hotbed of GCT development, ranking second in the world with more than 1,000 clinical trials either conducted or underway and thousands of related patents. It has a booming GCT biotech sector, led by more than 45 local companies with growing IND pipelines.
In late 1990, a T cell-based immunotherapy, cytokine-induced killer (CIK) therapy became a popular modality in the clinic in China for tumor treatment. In early 2010, Chinese researchers started to carry out domestic CAR T trials inspired by several important reports suggested the great antitumor function of CAR T cells. Now, China became the country with the most registered CAR T trials, CAR T therapy is flourishing in China.
The Chinese GCT ecosystem has increasingly rich local innovation and growing complement of development and investment partnerships – and also many subtleties.
This panel, consisting of leaders from the China GCT corporate, investor, research and entrepreneurial communities, will consider strategic questions on the growth of the gene and cell therapy industry in China, areas of greatest strength, evolving regulatory framework, early successes and products expected to reach the US and world market. Moderator: Min Wu, PhD
Managing Director, Fosun Health Fund
What are the area of CGT in China, regulatory similar to the US Speakers: Alvin Luk, PhD
CEO, Neuropath Therapeutics
Monogenic rare disease with clear genomic target
Increase of 30% in patient enrollment
Regulatory reform approval is 60 days no delayPin Wang, PhD
CSO, Jiangsu Simcere Pharmaceutical Co., Ltd.
Similar starting point in CGT as the rest of the World unlike a later starting point in other biologicalRichard Wang, PhD
CEO, Fosun Kite Biotechnology Co., Ltd
Possibilities to be creative and capitalize the new technologies for innovating drug
Support of the ecosystem by funding new companie allowing the industry to be developed in China
Autologous in patients differences cost challengeTian Xu, PhD
Vice President, Westlake University
ICH committee and Chinese FDA -r regulation similar to the US
Difference is the population recruitment, in China patients are active participants in skin disease
Active in development of transposome
Development of non-viral methods, CRISPR still in D and transposome
In China price of drugs regulatory are sensitive Shunfei Yan, PhD
The COVID vaccine race has propelled mRNA to the forefront of biomedicine. Long considered as a compelling modality for therapeutic gene transfer, the technology may have found its most impactful application as a vaccine platform. Given the transformative industrialization, the massive human experience, and the fast development that has taken place in this industry, where is the horizon? Does the success of the vaccine application, benefit or limit its use as a therapeutic for CGT?
How will the COVID success impact the rest of the industry both in therapeutic and prophylactic vaccines and broader mRNA lessons?
How will the COVID success impact the rest of the industry both on therapeutic and prophylactic vaccines and broader mRNA lessons?
Beyond from speed of development, what aspects make mRNA so well suited as a vaccine platform?
Will cost-of-goods be reduced as the industry matures?
How does mRNA technology seek to compete with AAV and other gene therapy approaches?
Many years of mRNA pivoting for new diseases, DARPA, nucleic Acids global deployment of a manufacturing unit on site where the need arise Elan Musk funds new directions at Moderna
How many mRNA can be put in one vaccine: Dose and tolerance to achieve efficacy
45 days for Personalized cancer vaccine one per patient
Hemophilia has been and remains a hallmark indication for the CGT. Given its well-defined biology, larger market, and limited need for gene transfer to provide therapeutic benefit, it has been at the forefront of clinical development for years, however, product approval remains elusive. What are the main hurdles to this success? Contrary to many indications that CGT pursues no therapeutic options are available to patients, hemophiliacs have an increasing number of highly efficacious treatment options. How does the competitive landscape impact this field differently than other CGT fields? With many different players pursuing a gene therapy option for hemophilia, what are the main differentiators? Gene therapy for hemophilia seems compelling for low and middle-income countries, given the cost of currently available treatments; does your company see opportunities in this market? Moderator: Nancy Berliner, MD
Safety concerns, high burden of treatment CGT has record of safety and risk/benefit adoption of Tx functional cure CGT is potent Tx relative small quantity of protein needs be delivered
Potency and quality less quantity drug and greater potency
risk of delivery unwanted DNA, capsules are critical
analytics is critical regulator involvement in potency definition
Director, Center for Rare Neurological Diseases, MGH
Associate Professor, Neurology, HMS
Single gene disorder NGS enable diagnosis, DIagnosis to Treatment How to know whar cell to target, make it available and scale up Address gap: missing components Biomarkers to cell types lipid chemistry cell animal biology
crosswalk from bone marrow matter
New gene discovered that causes neurodevelopment of stagnant genes Examining new Biology cell type specific biomarkers
The American Diabetes Association estimates 30 million Americans have diabetes and 1.5 million are diagnosed annually. GCT offers the prospect of long-sought treatment for this enormous cohort and their chronic requirements. The complexity of the disease and its management constitute a grand challenge and highlight both the potential of GCT and its current limitations.
Islet transplantation for type 1 diabetes has been attempted for decades. Problems like loss of transplanted islet cells due to autoimmunity and graft site factors have been difficult to address. Is there anything different on the horizon for gene and cell therapies to help this be successful?
How is the durability of response for gene or cell therapies for diabetes being addressed? For example, what would the profile of an acceptable (vs. optimal) cell therapy look like?
Advanced made, Patient of Type 1 Outer and Inner compartments of spheres (not capsule) no immune suppression continuous secretion of enzyme Insulin independence without immune suppression
Volume to have of-the-shelf inventory oxegenation in location lymphatic and vascularization conrol the whole process modular platform learning from others
Keep eyes open, waiting the Pandemic to end and enable working back on all the indications
Portfolio of MET, Mimi Emerging Therapies
Learning from the Pandemic – operationalize the practice science, R&D leaders, new collaboratives at NIH, FDA, Novartis
Pursue programs that will yield growth, tropic diseases with Gates Foundation, Rising Tide pods for access CGT within Novartis Partnership with UPenn in Cell Therapy
Cost to access to IP from Academia to a Biotech CRISPR accessing few translations to Clinic
Protein degradation organization constraint valuation by parties in a partnership
Novartis: nuclear protein lipid nuclear particles, tamplate for Biotech to collaborate
Game changing: 10% of the Portfolio, New frontiers human genetics in Ophthalmology, CAR-T, CRISPR, Gene Therapy Neurological and payloads of different matter
The Voice of Dr. Seidman – Her abstract is cited below
The ultimate opportunity presented by discovering the genetic basis of human disease is accurate prediction and disease prevention. To enable this achievement, genetic insights must enable the identification of at-risk
individuals prior to end-stage disease manifestations and strategies that delay or prevent clinical expression. Genetic cardiomyopathies provide a paradigm for fulfilling these opportunities. Hypertrophic cardiomyopathy (HCM) is characterized by left ventricular hypertrophy, diastolic dysfunction with normal or enhanced systolic performance and a unique histopathology: myocyte hypertrophy, disarray and fibrosis. Dilated cardiomyopathy (DCM) exhibits enlarged ventricular volumes with depressed systolic performance and nonspecific histopathology. Both HCM and DCM are prevalent clinical conditions that increase risk for arrhythmias, sudden death, and heart failure. Today treatments for HCM and DCM focus on symptoms, but none prevent disease progression. Human molecular genetic studies demonstrated that these pathologies often result from dominant mutations in genes that encode protein components of the sarcomere, the contractile unit in striated muscles. These data combined with the emergence of molecular strategies to specifically modulate gene expression provide unparalleled opportunities to silence or correct mutant genes and to boost healthy gene expression in patients with genetic HCM and DCM. Many challenges remain, but the active and vital efforts of physicians, researchers, and patients are poised to ensure success.
Cyprus Island, kidney disease by mutation causing MUC1 accumulation and death BRD4780 molecule that will clear the misfolding proteins from the kidney organoids: pleuripotent stem cells small molecule developed for applications in the other cell types in brain, eye, gene mutation build mechnism for therapy clinical models transition from Academia to biotech
One of the most innovative segments in all of healthcare is the development of GCT driven therapies for rare and ultra-rare diseases. Driven by a series of insights and tools and funded in part by disease focused foundations, philanthropists and abundant venture funding disease after disease is yielding to new GCT technology. These often become platforms to address more prevalent diseases. The goal of making these breakthroughs routine and affordable is challenged by a range of issues including clinical trial design and pricing.
What is driving the interest in rare diseases?
What are the biggest barriers to making breakthroughs ‘routine and affordable?’
What is the role of retrospective and prospective natural history studies in rare disease? When does the expected value of retrospective disease history studies justify the cost?
Related to the first question, what is the FDA expecting as far as controls in clinical trials for rare diseases? How does this impact the collection of natural history data?
The power of GCT to cure disease has the prospect of profoundly improving the lives of patients who respond. Planning for a disruption of this magnitude is complex and challenging as it will change care across the spectrum. Leading chief executives shares perspectives on how the industry will change and how this change should be anticipated. Moderator: Meg Tirrell
Senior Health and Science Reporter, CNBC
CGT becoming staple therapy what are the disruptors emerging Speakers: Lisa Dechamps
SVP & Chief Business Officer, Novartis Gene Therapies
Reimagine medicine with collaboration at MGH, MDM condition in children
The Science is there, sustainable processes and systems impact is transformational
Value based pricing, risk sharing Payers and Pharma for one time therapy with life span effect
Head, Pharmaceuticals Research & Development, Bayer AG
CGT – 2016 and in 2020 new leadership and capability
Disease Biology and therapeutics
Regenerative Medicine: CGT vs repair building pipeline in ophthalmology and cardiovascular
During Pandemic: Deliver Medicines like Moderna, Pfizer – collaborations between competitors with Government Bayer entered into Vaccines in 5 days, all processes had to change access innovations developed over decades for medical solutions
GCT represents a large and growing market for novel therapeutics that has several segments. These include Cardiovascular Disease, Cancer, Neurological Diseases, Infectious Disease, Ophthalmology, Benign Blood Disorders, and many others; Manufacturing and Supply Chain including CDMO’s and CMO’s; Stem Cells and Regenerative Medicine; Tools and Platforms (viral vectors, nano delivery, gene editing, etc.). Bayer’s pharma business participates in virtually all of these segments. How does a Company like Bayer approach the development of a portfolio in a space as large and as diverse as this one? How does Bayer approach the support of the production infrastructure with unique demands and significant differences from its historical requirements? Moderator:
EVP, Pharmaceuticals, Head of Cell & Gene Therapy, Bayer AG
CGT will bring treatment to cure, delivery of therapies
Be a Leader repair, regenerate, cure
Technology and Science for CGT – building a portfolio vs single asset decision criteria development of IP market access patients access acceleration of new products
Bayer strategy: build platform for use by four domains
Gener augmentation
Autologeneic therapy, analytics
Gene editing
Oncology Cell therapy tumor treatment: What kind of cells – the jury is out
Of 23 product launch at Bayer no prediction is possible some high some lows
Gene delivery uses physical, chemical, or viral means to introduce genetic material into cells. As more genetically modified therapies move closer to the market, challenges involving safety, efficacy, and manufacturing have emerged. Optimizing lipidic and polymer nanoparticles and exosomal delivery is a short-term priority. This panel will examine how the short-term and long-term challenges are being tackled particularly for non-viral delivery modalities. Moderator: Natalie Artzi, PhD
Gene editing was recognized by the Nobel Committee as “one of gene technology’s sharpest tools, having a revolutionary impact on life sciences.” Introduced in 2011, gene editing is used to modify DNA. It has applications across almost all categories of disease and is also being used in agriculture and public health.
Today’s panel is made up of pioneers who represent foundational aspects of gene editing. They will discuss the movement of the technology into the therapeutic mainstream.
Successes in gene editing – lessons learned from late-stage assets (sickle cell, ophthalmology)
When to use what editing tool – pros and cons of traditional gene-editing v. base editing. Is prime editing the future? Specific use cases for epigenetic editing.
When we reach widespread clinical use – role of off-target editing – is the risk real? How will we mitigate? How practical is patient-specific off-target evaluation?
There are several dozen companies working to develop gene or cell therapies for Sickle Cell Disease, Beta Thalassemia, and Fanconi Anemia. In some cases, there are enzyme replacement therapies that are deemed effective and safe. In other cases, the disease is only managed at best. This panel will address a number of questions that are particular to this class of genetic diseases:
What are the pros and cons of various strategies for treatment? There are AAV-based editing, non-viral delivery even oligonucleotide recruitment of endogenous editing/repair mechanisms. Which approaches are most appropriate for which disease?
How can companies increase the speed of recruitment for clinical trials when other treatments are available? What is the best approach to educate patients on a novel therapeutic?
How do we best address ethnic and socio-economic diversity to be more representative of the target patient population?
How long do we have to follow up with the patients from the scientific, patient’s community, and payer points of view? What are the current FDA and EMA guidelines for long-term follow-up?
Where are we with regards to surrogate endpoints and their application to clinically meaningful endpoints?
What are the emerging ethical dilemmas in pediatric gene therapy research? Are there challenges with informed consent and pediatric assent for trial participation?
Are there differences in reimbursement policies for these different blood disorders? Clearly durability of response is a big factor. Are there other considerations?
Oligonucleotide drugs have recently come into their own with approvals from companies such as Biogen, Alnylam, Novartis and others. This panel will address several questions:
How important is the delivery challenge for oligonucleotides? Are technological advancements emerging that will improve the delivery of oligonucleotides to the CNS or skeletal muscle after systemic administration?
Will oligonucleotides improve as a class that will make them even more effective? Are further advancements in backbone chemistry anticipated, for example.
Will oligonucleotide based therapies blaze trails for follow-on gene therapy products?
Are small molecules a threat to oligonucleotide-based therapies?
Beyond exon skipping and knock-down mechanisms, what other roles will oligonucleotide-based therapies take mechanistically — can genes be activating oligonucleotides? Is there a place for multiple mechanism oligonucleotide medicines?
Are there any advantages of RNAi-based oligonucleotides over ASOs, and if so for what use?
What is occurring in the GCT venture capital segment? Which elements are seeing the most activity? Which areas have cooled? How is the investment market segmented between gene therapy, cell therapy and gene editing? What makes a hot GCT company? How long will the market stay frothy? Some review of demographics — # of investments, sizes, etc. Why is the market hot and how long do we expect it to stay that way? Rank the top 5 geographic markets for GCT company creation and investing? Are there academic centers that have been especially adept at accelerating GCT outcomes? Do the business models for the rapid development of coronavirus vaccine have any lessons for how GCT technology can be brought to market more quickly? Moderator: Meredith Fisher, PhD
The promise of stem cells has been a highlight in the realm of regenerative medicine. Unfortunately, that promise remains largely in the future. Recent breakthroughs have accelerated these potential interventions in particular for treating neurological disease. Among the topics the panel will consider are:
Stem cell sourcing
Therapeutic indication growth
Genetic and other modification in cell production
Cell production to final product optimization and challenges
The dynamics of venture/PE investing and IPOs are fast evolving. What are the drivers – will the number of investors grow will the size of early rounds continue to grow? How is this reflected in GCT target areas, company design, and biotech overall? Do patients benefit from these trends? Is crossover investing a distinct class or a little of both? Why did it emerge and what are the characteristics of the players? Will SPACs play a role in the growth of the gene and cell therapy industry. What is the role of corporate investment arms eg NVS, Bayer, GV, etc. – has a category killer emerged? Are we nearing the limit of what the GCT market can absorb or will investment capital continue to grow unabated? Moderator: Roger Kitterman
Nearly one hundred senior Mass General Brigham Harvard faculty contributed to the creation of this group of twelve GCT technologies that they believe will breakthrough in the next two years. The Disruptive Dozen identifies and ranks the GCT technologies that will be available on at least an experimental basis to have the chance of significantly improving health care. 11:35 AM – 11:45 AM
Computer connection to the iCloud of WordPress.com FROZE completely at 10:30AM EST and no file update was possible. COVERAGE OF MAY 21, 2021 IS RECORDED BELOW FOLLOWING THE AGENDA BY COPY AN DPASTE OF ALL THE TWEETS I PRODUCED ON MAY 21, 2021 8:30 AM – 8:55 AM
What is occurring in the GCT venture capital segment? Which elements are seeing the most activity? Which areas have cooled? How is the investment market segmented between gene therapy, cell therapy and gene editing? What makes a hot GCT company? How long will the market stay frothy? Some review of demographics — # of investments, sizes, etc. Why is the market hot and how long do we expect it to stay that way? Rank the top 5 geographic markets for GCT company creation and investing? Are there academic centers that have been especially adept at accelerating GCT outcomes? Do the business models for the rapid development of coronavirus vaccine have any lessons for how GCT technology can be brought to market more quickly? Moderator: Meredith Fisher, PhD
The promise of stem cells has been a highlight in the realm of regenerative medicine. Unfortunately, that promise remains largely in the future. Recent breakthroughs have accelerated these potential interventions in particular for treating neurological disease. Among the topics the panel will consider are:
Stem cell sourcing
Therapeutic indication growth
Genetic and other modification in cell production
Cell production to final product optimization and challenges
The dynamics of venture/PE investing and IPOs are fast evolving. What are the drivers – will the number of investors grow will the size of early rounds continue to grow? How is this reflected in GCT target areas, company design, and biotech overall? Do patients benefit from these trends? Is crossover investing a distinct class or a little of both? Why did it emerge and what are the characteristics of the players? Will SPACs play a role in the growth of the gene and cell therapy industry. What is the role of corporate investment arms eg NVS, Bayer, GV, etc. – has a category killer emerged? Are we nearing the limit of what the GCT market can absorb or will investment capital continue to grow unabated? Moderator: Roger Kitterman
Nearly one hundred senior Mass General Brigham Harvard faculty contributed to the creation of this group of twelve GCT technologies that they believe will breakthrough in the next two years. The Disruptive Dozen identifies and ranks the GCT technologies that will be available on at least an experimental basis to have the chance of significantly improving health care. 11:35 AM – 11:45 AM
The co-chairs convene to reflect on the insights shared over the three days. They will discuss what to expect at the in-person GCT focused May 2-4, 2022 World Medical Innovation Forum.
The co-chairs convene to reflect on the insights shared over the three days. They will discuss what to expect at the in-person GCT focused May 2-4, 2022 World Medical Innovation Forum.Christine Seidman, MD
Cyprus Island, kidney disease by mutation causing MUC1 accumulation and death BRD4780 molecule that will clear the misfolding proteins from the kidney organoids: pleuripotent stem cells small molecule developed for applications in the other cell types in brain, eye, gene mutation build mechnism for therapy clinical models transition from Academia to biotech
One of the most innovative segments in all of healthcare is the development of GCT driven therapies for rare and ultra-rare diseases. Driven by a series of insights and tools and funded in part by disease focused foundations, philanthropists and abundant venture funding disease after disease is yielding to new GCT technology. These often become platforms to address more prevalent diseases. The goal of making these breakthroughs routine and affordable is challenged by a range of issues including clinical trial design and pricing.
What is driving the interest in rare diseases?
What are the biggest barriers to making breakthroughs ‘routine and affordable?’
What is the role of retrospective and prospective natural history studies in rare disease? When does the expected value of retrospective disease history studies justify the cost?
Related to the first question, what is the FDA expecting as far as controls in clinical trials for rare diseases? How does this impact the collection of natural history data?
The power of GCT to cure disease has the prospect of profoundly improving the lives of patients who respond. Planning for a disruption of this magnitude is complex and challenging as it will change care across the spectrum. Leading chief executives shares perspectives on how the industry will change and how this change should be anticipated. Moderator: Meg Tirrell
Senior Health and Science Reporter, CNBC
CGT becoming staple therapy what are the disruptors emerging Speakers: Lisa Dechamps
SVP & Chief Business Officer, Novartis Gene Therapies
Reimagine medicine with collaboration at MGH, MDM condition in children
The Science is there, sustainable processes and systems impact is transformational
Value based pricing, risk sharing Payers and Pharma for one time therapy with life span effect
Head, Pharmaceuticals Research & Development, Bayer AG
CGT – 2016 and in 2020 new leadership and capability
Disease Biology and therapeutics
Regenerative Medicine: CGT vs repair building pipeline in ophthalmology and cardiovascular
During Pandemic: Deliver Medicines like Moderna, Pfizer – collaborations between competitors with Government Bayer entered into Vaccines in 5 days, all processes had to change access innovations developed over decades for medical solutions
GCT represents a large and growing market for novel therapeutics that has several segments. These include Cardiovascular Disease, Cancer, Neurological Diseases, Infectious Disease, Ophthalmology, Benign Blood Disorders, and many others; Manufacturing and Supply Chain including CDMO’s and CMO’s; Stem Cells and Regenerative Medicine; Tools and Platforms (viral vectors, nano delivery, gene editing, etc.). Bayer’s pharma business participates in virtually all of these segments. How does a Company like Bayer approach the development of a portfolio in a space as large and as diverse as this one? How does Bayer approach the support of the production infrastructure with unique demands and significant differences from its historical requirements? Moderator:
EVP, Pharmaceuticals, Head of Cell & Gene Therapy, Bayer AG
CGT will bring treatment to cure, delivery of therapies
Be a Leader repair, regenerate, cure
Technology and Science for CGT – building a portfolio vs single asset decision criteria development of IP market access patients access acceleration of new products
Bayer strategy: build platform for use by four domains
Gener augmentation
Autologeneic therapy, analytics
Gene editing
Oncology Cell therapy tumor treatment: What kind of cells – the jury is out
Of 23 product launch at Bayer no prediction is possible some high some lows
Gene delivery uses physical, chemical, or viral means to introduce genetic material into cells. As more genetically modified therapies move closer to the market, challenges involving safety, efficacy, and manufacturing have emerged. Optimizing lipidic and polymer nanoparticles and exosomal delivery is a short-term priority. This panel will examine how the short-term and long-term challenges are being tackled particularly for non-viral delivery modalities. Moderator: Natalie Artzi, PhD
Gene editing was recognized by the Nobel Committee as “one of gene technology’s sharpest tools, having a revolutionary impact on life sciences.” Introduced in 2011, gene editing is used to modify DNA. It has applications across almost all categories of disease and is also being used in agriculture and public health.
Today’s panel is made up of pioneers who represent foundational aspects of gene editing. They will discuss the movement of the technology into the therapeutic mainstream.
Successes in gene editing – lessons learned from late-stage assets (sickle cell, ophthalmology)
When to use what editing tool – pros and cons of traditional gene-editing v. base editing. Is prime editing the future? Specific use cases for epigenetic editing.
When we reach widespread clinical use – role of off-target editing – is the risk real? How will we mitigate? How practical is patient-specific off-target evaluation?
There are several dozen companies working to develop gene or cell therapies for Sickle Cell Disease, Beta Thalassemia, and Fanconi Anemia. In some cases, there are enzyme replacement therapies that are deemed effective and safe. In other cases, the disease is only managed at best. This panel will address a number of questions that are particular to this class of genetic diseases:
What are the pros and cons of various strategies for treatment? There are AAV-based editing, non-viral delivery even oligonucleotide recruitment of endogenous editing/repair mechanisms. Which approaches are most appropriate for which disease?
How can companies increase the speed of recruitment for clinical trials when other treatments are available? What is the best approach to educate patients on a novel therapeutic?
How do we best address ethnic and socio-economic diversity to be more representative of the target patient population?
How long do we have to follow up with the patients from the scientific, patient’s community, and payer points of view? What are the current FDA and EMA guidelines for long-term follow-up?
Where are we with regards to surrogate endpoints and their application to clinically meaningful endpoints?
What are the emerging ethical dilemmas in pediatric gene therapy research? Are there challenges with informed consent and pediatric assent for trial participation?
Are there differences in reimbursement policies for these different blood disorders? Clearly durability of response is a big factor. Are there other considerations?
Oligonucleotide drugs have recently come into their own with approvals from companies such as Biogen, Alnylam, Novartis and others. This panel will address several questions:
How important is the delivery challenge for oligonucleotides? Are technological advancements emerging that will improve the delivery of oligonucleotides to the CNS or skeletal muscle after systemic administration?
Will oligonucleotides improve as a class that will make them even more effective? Are further advancements in backbone chemistry anticipated, for example.
Will oligonucleotide based therapies blaze trails for follow-on gene therapy products?
Are small molecules a threat to oligonucleotide-based therapies?
Beyond exon skipping and knock-down mechanisms, what other roles will oligonucleotide-based therapies take mechanistically — can genes be activating oligonucleotides? Is there a place for multiple mechanism oligonucleotide medicines?
Are there any advantages of RNAi-based oligonucleotides over ASOs, and if so for what use?
Computer connection to the iCloud of WordPress.com FROZE completely at 10:30AM EST and no file update was possible. COVERAGE OF MAY 21, 2021 IS RECORDED BELOW FOLLOWING THE AGENDA BY COPY AN DPASTE OF ALL THE TWEETS I PRODUCED ON MAY 21, 2021
What is occurring in the GCT venture capital segment? Which elements are seeing the most activity? Which areas have cooled? How is the investment market segmented between gene therapy, cell therapy and gene editing? What makes a hot GCT company? How long will the market stay frothy? Some review of demographics — # of investments, sizes, etc. Why is the market hot and how long do we expect it to stay that way? Rank the top 5 geographic markets for GCT company creation and investing? Are there academic centers that have been especially adept at accelerating GCT outcomes? Do the business models for the rapid development of coronavirus vaccine have any lessons for how GCT technology can be brought to market more quickly? Moderator: Meredith Fisher, PhD
Partner, Mass General Brigham Innovation Fund
Strategies, success what changes are needed in the drug discovery process Speakers:
Bring disruptive frontier as a platform with reliable delivery CGT double knock out disease cure all change efficiency and scope human centric vs mice centered right scale of data converted into therapeutics acceleratetion
Innovation in drugs 60% fails in trial because of Toxicology system of the future deal with big diseases
Moderna is an example in unlocking what is inside us Microbiome and beyond discover new drugs epigenetics
Manufacturing change is not a new clinical trial FDA need to be presented with new rethinking for big innovations Drug pricing cheaper requires systematization How to systematically scaling up systematize the discovery and the production regulatory innovations
The promise of stem cells has been a highlight in the realm of regenerative medicine. Unfortunately, that promise remains largely in the future. Recent breakthroughs have accelerated these potential interventions in particular for treating neurological disease. Among the topics the panel will consider are:
Stem cell sourcing
Therapeutic indication growth
Genetic and other modification in cell production
Cell production to final product optimization and challenges
Director, Neuroregeneration Research Institute, McLean
Professor, Neurology and Neuroscience, MGH, HMS
Opportunities in the next generation of the tactical level Welcome the oprimism and energy level of all Translational medicine funding stem cells enormous opportunities
Ear inside the scall compartments and receptors responsible for hearing highly differentiated tall ask to identify cell for anticipated differentiation
The dynamics of venture/PE investing and IPOs are fast evolving. What are the drivers – will the number of investors grow will the size of early rounds continue to grow? How is this reflected in GCT target areas, company design, and biotech overall? Do patients benefit from these trends? Is crossover investing a distinct class or a little of both? Why did it emerge and what are the characteristics of the players? Will SPACs play a role in the growth of the gene and cell therapy industry. What is the role of corporate investment arms eg NVS, Bayer, GV, etc. – has a category killer emerged? Are we nearing the limit of what the GCT market can absorb or will investment capital continue to grow unabated? Moderator: Roger Kitterman
VP, Venture, Mass General Brigham
Saturation reached or more investment is coming in CGT
Pharmacologic agent in existing cause another disorders locomo-movement related
efficacy Autologous cell therapy transplantation approach program T cells into dopamine generating neurons greater than Allogeneic cell transplantation
Current market does not have delivery mechanism that a drug-delivery is the solution Trials would fail on DELIVERY
Immune suppressed patients during one year to avoid graft rejection Autologous approach of Parkinson patient genetically mutated reprogramed as dopamine generating neuron – unknowns are present
Circuitry restoration
Microenvironment disease ameliorate symptoms – education of patients on the treatment
Nearly one hundred senior Mass General Brigham Harvard faculty contributed to the creation of this group of twelve GCT technologies that they believe will breakthrough in the next two years. The Disruptive Dozen identifies and ranks the GCT technologies that will be available on at least an experimental basis to have the chance of significantly improving health care. 11:35 AM – 11:45 AM
The co-chairs convene to reflect on the insights shared over the three days. They will discuss what to expect at the in-person GCT focused May 2-4, 2022 World Medical Innovation Forum.
ALL THE TWEETS PRODUCED ON MAY 21, 2021 INCLUDE THE FOLLOWING:
Bob Carter, MD, PhD Chairman, Department of Neurosurgery, MGH William and Elizabeth Sweet, Professor of Neurosurgery, HMS Neurogeneration REVERSAL or slowing down?
Penelope Hallett, PhD NRL, McLean Assistant Professor Psychiatry, HMS efficacy Autologous cell therapy transplantation approach program T cells into dopamine genetating cells greater than Allogeneic cell transplantation
Roger Kitterman VP, Venture, Mass General Brigham Saturation reached or more investment is coming in CGT Multi OMICS and academia originated innovations are the most attractive areas
Peter Kolchinsky, PhD Founder and Managing Partner, RA Capital Management Future proof for new comers disruptors Ex Vivo gene therapy to improve funding products what tool kit belongs to
Chairman, Department of Neurosurgery, MGH, Professor of Neurosurgery, HMS Cell therapy for Parkinson to replace dopamine producing cells lost ability to produce dopamine skin cell to become autologous cells reprogramed
Kapil Bharti, PhD Senior Investigator, Ocular and Stem Cell Translational Research Section, NIH Off-th-shelf one time treatment becoming cure Intact tissue in a dish is fragile to maintain metabolism to become like semiconductors
Ole Isacson, MD, PhD Director, Neuroregeneration Research Institute, McLean Professor, Neurology and Neuroscience, MGH, HMS Opportunities in the next generation of the tactical level Welcome the oprimism and energy level of all
Erin Kimbrel, PhD Executive Director, Regenerative Medicine, Astellas In the ocular space immunogenecity regulatory communication use gene editing for immunogenecity Cas1 and Cas2 autologous cells
Nabiha Saklayen, PhD CEO and Co-Founder, Cellino scale production of autologous cells foundry using semiconductor process in building cassettes by optic physicists
Joe Burns, PhD VP, Head of Biology, Decibel Therapeutics Ear inside the scall compartments and receptors responsible for hearing highly differentiated tall ask to identify cell for anticipated differentiation control by genomics
Kapil Bharti, PhD Senior Investigator, Ocular and Stem Cell Translational Research Section, NIH first drug required to establish the process for that innovations design of animal studies not done before
Robert Nelsen Managing Director, Co-founder, ARCH Venture Partners Manufacturing change is not a new clinical trial FDA need to be presented with new rethinking for big innovations Drug pricing cheaper requires systematization
David Berry, MD, PhD CEO, Valo Health GP, Flagship Pioneering Bring disruptive frontier platform reliable delivery CGT double knockout disease cure all change efficiency scope human centric vs mice centered right scale acceleration
Kush Parmar, MD, PhD Managing Partner, 5AM Ventures build it yourself, benefit for patients FIrst Look at MGB shows MEE innovation on inner ear worthy investment
Robert Nelsen Managing Director, Co-founder, ARCH Venture Partners Frustration with supply chain during the Pandemic, GMC anticipation in advance CGT rapidly prototype rethink and invest proactive investor .edu and Pharma
Happy 80th Birthday: Radioiodine (RAI) Theranostics: Collaboration between Physics and Medicine, the Utilization of Radionuclides to Diagnose and Treat: Radiation Dosimetry by Discoverer Dr. Saul Hertz, the early history of RAI in diagnosing and treating Thyroid diseases and Theranostics
Both authors contributed to the development, drafting and final editing of this manuscript and are responsible for its content.
Abstract
March 2021 will mark the eightieth anniversary of targeted radionuclide therapy, recognizing the first use of radioactive iodine to treat thyroid disease by Dr. Saul Hertz on March 31, 1941. The breakthrough of Dr. Hertz and collaborator physicist Arthur Roberts was made possible by rapid developments in the fields of physics and medicine in the early twentieth century. Although diseases of the thyroid gland had been described for centuries, the role of iodine in thyroid physiology had been elucidated only in the prior few decades. After the discovery of radioactivity by Henri Becquerel in 1897, rapid advancements in the field, including artificial production of radioactive isotopes, were made in the subsequent decades. Finally, the diagnostic and therapeutic use of radioactive iodine was based on the tracer principal that was developed by George de Hevesy. In the context of these advancements, Hertz was able to conceive the potential of using of radioactive iodine to treat thyroid diseases. Working with Dr. Roberts, he obtained the experimental data and implemented it in the clinical setting. Radioiodine therapy continues to be a mainstay of therapy for hyperthyroidism and thyroid cancer. However, Hertz struggled to gain recognition for his accomplishments and to continue his work and, with his early death in 1950, his contributions have often been overlooked until recently. The work of Hertz and others provided a foundation for the introduction of other radionuclide therapies and for the development of the concept of theranostics.
Dr. Saul Hertz was Director of The Massachusetts General Hospital’s Thyroid Unit, when he heard about the development of artificial radioactivity. He conceived and brought from bench to bedside the successful use of radioiodine (RAI) to diagnose and treat thyroid diseases. Thus was born the science of theragnostics used today for neuroendocrine tumors and prostate cancer. Dr. Hertz’s work set the foundation of targeted precision medicine.
Keywords: Dr. Saul Hertz, nuclear medicine, radioiodine
How to cite this article:
Hertz B. A tribute to Dr. Saul Hertz: The discovery of the medical uses of radioiodine. World J Nucl Med 2019;18:8-12
How to cite this URL:
Hertz B. A tribute to Dr. Saul Hertz: The discovery of the medical uses of radioiodine. World J Nucl Med [serial online] 2019 [cited 2021 Mar 2];18:8-12. Available from: http://www.wjnm.org/text.asp?2019/18/1/8/250309
Dr Saul Hertz (1905-1950) discovers the medical uses of radioiodine
Barbara Hertz, Pushan Bharadwaj, Bennett Greenspan»
Thyroid practitioners and patients are acutely aware of the enormous benefit nuclear medicine has made to mankind. This month we celebrate the 80th anniversary of the early use of radioiodine(RAI).
Dr. Saul Hertz predicted that radionuclides “…would hold the key to the larger problem of cancer in general,” and may just be the best hope for diagnosing and treating cancer successfully. Yes, RAI has been used for decades to diagnose and treat disease. Today’s “theranostics,” a term that is a combination of “therapy” and “diagnosis” is utilized in the treatment of thyroid disease and cancer.
This short note is to celebrate Dr. Saul Hertz who conceived and brought from bench to bedside the medical uses of RAI; then in the form of 25 minute iodine-128.
On March 31st 1941, Massachusetts General Hospital’s Dr. Saul Hertz (1905-1950) administered the first therapeutic use of Massachusetts Institute of Technology (MIT) cyclotron produced RAI. This landmark case was the first in Hertz’s clinical studies conducted with MIT, physicist Arthur Roberts, Ph.D.
[Photo – Courtesy of Dr Saul Hertz Archives ]
Dr Saul Hertz demonstrating RAI Uptake Testing
Dr. Hertz’s research and successful utilization of radionuclides to diagnose and treat diseases and conditions, established the use of radiation dosimetry and the collaboration between physics and medicine and other significant practices. Sadly, Saul Hertz (a WWII veteran) died at a very young age.
About Dr. Saul Hertz
Dr. Saul Hertz (1905 – 1950) discovered the medical uses of radionuclides. His breakthrough work with radioactive iodine (RAI) created a dynamic paradigym change integrating the sciences. Radioactive iodine (RAI) is the first and Gold Standard of targeted cancer therapies. Saul Hertz’s research documents Hertz as the first and foremost person to conceive and develop the experimental data on RAI and apply it in the clinical setting.
Dr. Hertz was born to Orthodox Jewish immigrant parents in Cleveland, Ohio on April 20, 1905. He received his A.B. from the University of Michigan in 1925 with Phi Beta Kappa honors. He graduated from Harvard Medical School in 1929 at a time of quotas for outsiders. He fulfilled his internship and residency at Mt. Sinai Hospital in Cleveland. He came back to Boston in 1931 as a volunteer to join The Massachusetts General Hospital serving as the Chief of the Thyroid Unit from 1931 – 1943.
Two years after the discovery of artifically radioactivity, on November 12, 1936 Dr. Karl Compton, president of the Massachusetts Institute of Technology (MIT), spoke at Harvard Medical School. President Compton’s topic was What Physics can do for Biology and Medicine. After the presentation Dr. Hertz spontaneously asked Dr. Compton this seminal question, “Could iodine be made radioactive artificially?” Dr. Compton responded in writing on December 15, 1936 that in fact “iodine can be made artificially radioactive.”
Shortly thereafter, a collaboration between Dr. Hertz (MGH) and Dr. Arthur Roberts, a physicist of MIT, was established. In late 1937, Hertz and Roberts created and produced animal studies involving 48 rabbits that demonstrated that the normal thyroid gland concentrated Iodine 128 (non cyclotron produced), and the hyperplastic thyroid gland took up even more Iodine. This was a GIANT step for Nuclear Medicine.
In early 1941, Dr. Hertz administer the first therapeutic treatment of MIT Markle Cyclotron produced radioactive iodine (RAI) at the Massachusetts General Hospital. This led to the first series of twenty-nine patients with hyperthyroidism being treated successfully with RAI. ( see “Research” RADIOACTIVE IODINE IN THE STUDY OF THYROID PHYSIOLOGY VII The use of Radioactive Iodine Therapy in Hyperthyroidism, Saul Hertz and Arthur Roberts, JAMA Vol. 31 Number 2).
In 1937, at the time of the rabbit studies Dr Hertz conceived of RAI in therapeutic treatment of thyroid carsonoma. In 1942 Dr Hertz gave clinical trials of RAI to patients with thyroid carcinoma.
After serving in the Navy during World War II, Dr. Hertz wrote to the director of the Mass General Hospital in Boston, Dr. Paxon on March 12, 1946, “it is a coincidence that my new research project is in Cancer of the Thyroid, which I believe holds the key to the larger problem of cancer in general.”
Dr. Hertz established the Radioactive Isotope Research Institute, in September, 1946 with a major focus on the use of fission products for the treatment of thyroid cancer, goiter, and other malignant tumors. Dr Samuel Seidlin was the Associate Director and managed the New York City facilities. Hertz also researched the influence of hormones on cancer.
Dr. Hertz’s use of radioactive iodine as a tracer in the diagnostic process, as a treatment for Graves’ disease and in the treatment of cancer of the thyroid remain preferred practices. Saul Hertz is the Father of Theranostics.
Saul Hertz passed at 45 years old from a sudden death heart attack as documented by an autopsy. He leaves an enduring legacy impacting countless generations of patients, numerous institutions worldwide and setting the cornerstone for the field of Nuclear Medicine. A cancer survivor emailed, The cure delivered on the wings of prayer was Dr Saul Hertz’s discovery, the miracle of radioactive iodine. Few can equal such a powerful and precious gift.
To read and hear more about Dr. Hertz and the early history of RAI in diagnosing and treating thyroid diseases and theranostics see –
Hertz S, Roberts A. Radioactive iodine in the study of thyroid physiology. VII The use of radioactive iodine therapy in hyperthyroidism. J Am Med Assoc 1946;131:81-6.
Hertz S. A plan for analysis of the biologic factors involved in experimental carcinogenesis of the thyroid by means of radioactive isotopes. Bull New Engl Med Cent 1946;8:220-4.
Thrall J. The Story of Saul Hertz, Radioiodine and the Origins of Nuclear Medicine. Available from: http://www.youtube.com/watch?v=34Qhm8CeMuc. [Last accessed on 2018 Dec 01].
Krolicki L, Morgenstern A, Kunikowska J, Koiziar H, Krolicki B, Jackaniski M, et al. Glioma Tumors Grade II/III-Local Alpha Emitters Targeted Therapy with 213 Bi-DOTA-Substance P, Endocrine Abstracts. Vol. 57. Society of Nuclear Medicine and Molecular Imaging; 2016. p. 632.
Baum RP, Kulkarni HP. Duo PRRT of neuroendocrine tumours using concurrent and sequential administration of Y-90- and Lu-177-labeled somatostatin analogues. In: Hubalewska-Dydejczyk A, Signore A, de Jong M, Dierckx RA, Buscombe J, Van de Wiel CJ, editors. Somatostatin Analogues from Research to Clinical Practice. New York: Wiley; 2015.
Use of 3D Bioprinting for Development of Toxicity Prediction Models
Curator: Stephen J. Williams, PhD
SOT FDA Colloquium on 3D Bioprinted Tissue Models: Tuesday, April 9, 2019
The Society of Toxicology (SOT) and the U.S. Food and Drug Administration (FDA) will hold a workshop on “Alternative Methods for Predictive Safety Testing: 3D Bioprinted Tissue Models” on Tuesday, April 9, at the FDA Center for Food Safety and Applied Nutrition in College Park, Maryland. This workshop is the latest in the series, “SOT FDA Colloquia on Emerging Toxicological Science: Challenges in Food and Ingredient Safety.”
Human 3D bioprinted tissues represent a valuable in vitro approach for chemical, personal care product, cosmetic, and preclinical toxicity/safety testing. Bioprinting of skin, liver, and kidney is already appearing in toxicity testing applications for chemical exposures and disease modeling. The use of 3D bioprinted tissues and organs may provide future alternative approaches for testing that may more closely resemble and simulate intact human tissues to more accurately predict human responses to chemical and drug exposures.
A synopsis of the schedule and related works from the speakers is given below:
8:40 AM–9:20 AM
Overview and Challenges of Bioprinting
Sharon Presnell, Amnion Foundation, Winston-Salem, NC
9:20 AM–10:00 AM
Putting 3D Bioprinting to the Use of Tissue Model Fabrication
Y. Shrike Zhang, Brigham and Women’s Hospital, Harvard Medical School and Harvard-MIT Division of Health Sciences and Technology, Boston, MA
10:00 AM–10:20 AM
Break
10:20 AM–11:00 AM
Uses of Bioprinted Liver Tissue in Drug Development
Jean-Louis Klein, GlaxoSmithKline, Collegeville, PA
11:00 AM–11:40 AM
Biofabrication of 3D Tissue Models for Disease Modeling and Chemical Screening
Marc Ferrer, National Center for Advancing Translational Sciences, NIH, Rockville, MD
Dr. Sharon Presnell was most recently the Chief Scientific Officer at Organovo, Inc., and the President of their wholly-owned subsidiary, Samsara Sciences. She received a Ph.D. in Cell & Molecular Pathology from the Medical College of Virginia and completed her undergraduate degree in biology at NC State. In addition to her most recent roles, Presnell has served as the director of cell biology R&D at Becton Dickinson’s corporate research center in RTP, and as the SVP of R&D at Tengion. Her roles have always involved the commercial and clinical translation of basic research and early development in the cell biology space. She serves on the board of the Coulter Foundation at the University of Virginia and is a member of the College of Life Sciences Foundation Board at NC State. In January 2019, Dr. Presnell will begin a new role as President of the Amnion Foundation, a non-profit organization in Winston-Salem.
Integrating Kupffer cells into a 3D bioprinted model of human liver recapitulates fibrotic responses of certain toxicants in a time and context dependent manner. This work establishes that the presence of Kupffer cells or macrophages are important mediators in fibrotic responses to certain hepatotoxins and both should be incorporated into bioprinted human liver models for toxicology testing.
Abstract: Modeling clinically relevant tissue responses using cell models poses a significant challenge for drug development, in particular for drug induced liver injury (DILI). This is mainly because existing liver models lack longevity and tissue-level complexity which limits their utility in predictive toxicology. In this study, we established and characterized novel bioprinted human liver tissue mimetics comprised of patient-derived hepatocytes and non-parenchymal cells in a defined architecture. Scaffold-free assembly of different cell types in an in vivo-relevant architecture allowed for histologic analysis that revealed distinct intercellular hepatocyte junctions, CD31+ endothelial networks, and desmin positive, smooth muscle actin negative quiescent stellates. Unlike what was seen in 2D hepatocyte cultures, the tissues maintained levels of ATP, Albumin as well as expression and drug-induced enzyme activity of Cytochrome P450s over 4 weeks in culture. To assess the ability of the 3D liver cultures to model tissue-level DILI, dose responses of Trovafloxacin, a drug whose hepatotoxic potential could not be assessed by standard pre-clinical models, were compared to the structurally related non-toxic drug Levofloxacin. Trovafloxacin induced significant, dose-dependent toxicity at clinically relevant doses (≤ 4uM). Interestingly, Trovafloxacin toxicity was observed without lipopolysaccharide stimulation and in the absence of resident macrophages in contrast to earlier reports. Together, these results demonstrate that 3D bioprinted liver tissues can both effectively model DILI and distinguish between highly related compounds with differential profile. Thus, the combination of patient-derived primary cells with bioprinting technology here for the first timedemonstrates superior performance in terms of mimicking human drug response in a known target organ at the tissue level.
A great interview with Dr. Presnell and the 3D Models 2017 Symposium is located here:
Please clickhere for Web based and PDF version of interview
Some highlights of the interview include
Exciting advances in field showing we can model complex tissue-level disease-state phenotypes that develop in response to chronic long term injury or exposure
Sees the field developing a means to converge both the biology and physiology of tissues, namely modeling the connectivity between tissues such as fluid flow
Future work will need to be dedicated to develop comprehensive analytics for 3D tissue analysis. As she states “we are very conditioned to get information in a simple way from biochemical readouts in two dimension, monocellular systems” however how we address the complexity of various cellular responses in a 3D multicellular environment will be pertinent.
Additional challenges include the scalability of such systems and making such system accessible in a larger way
Shrike Zhang, Brigham and Women’s Hospital, Harvard Medical School and Harvard-MIT Division of Health Sciences and Technology
Dr. Zhang currently holds an Assistant Professor position at Harvard Medical School and is an Associate Bioengineer at Brigham and Women’s Hospital. His research interests include organ-on-a-chip, 3D bioprinting, biomaterials, regenerative engineering, biomedical imaging, biosensing, nanomedicine, and developmental biology. His scientific contributions have been recognized by >40 international, national, and regional awards. He has been invited to deliver >70 lectures worldwide, and has served as reviewer for >400 manuscripts for >30 journals. He is serving as Editor-in-Chief for Microphysiological Systems, and Associate Editor for Bio-Design and Manufacturing. He is also on Editorial Board of Bioprinting, Heliyon, BMC Materials, and Essays in Biochemistry, and on Advisory Panel of Nanotechnology.
Skardal A, Murphy SV, Devarasetty M, Mead I, Kang HW, Seol YJ, Shrike Zhang Y, Shin SR, Zhao L, Aleman J, Hall AR, Shupe TD, Kleensang A, Dokmeci MR, Jin Lee S, Jackson JD, Yoo JJ, Hartung T, Khademhosseini A, Soker S, Bishop CE, Atala A.
Sci Rep. 2017 Aug 18;7(1):8837. doi: 10.1038/s41598-017-08879-x.
Bhise NS, Manoharan V, Massa S, Tamayol A, Ghaderi M, Miscuglio M, Lang Q, Shrike Zhang Y, Shin SR, Calzone G, Annabi N, Shupe TD, Bishop CE, Atala A, Dokmeci MR, Khademhosseini A.
Biofabrication. 2016 Jan 12;8(1):014101. doi: 10.1088/1758-5090/8/1/014101.
Marc Ferrer, National Center for Advancing Translational Sciences, NIH
Marc Ferrer is a team leader in the NCATS Chemical Genomics Center, which was part of the National Human Genome Research Institute when Ferrer began working there in 2010. He has extensive experience in drug discovery, both in the pharmaceutical industry and academic research. Before joining NIH, he was director of assay development and screening at Merck Research Laboratories. For 10 years at Merck, Ferrer led the development of assays for high-throughput screening of small molecules and small interfering RNA (siRNA) to support programs for lead and target identification across all disease areas.
At NCATS, Ferrer leads the implementation of probe development programs, discovery of drug combinations and development of innovative assay paradigms for more effective drug discovery. He advises collaborators on strategies for discovering small molecule therapeutics, including assays for screening and lead identification and optimization. Ferrer has experience implementing high-throughput screens for a broad range of disease areas with a wide array of assay technologies. He has led and managed highly productive teams by setting clear research strategies and goals and by establishing effective collaborations between scientists from diverse disciplines within industry, academia and technology providers.
Ferrer has a Ph.D. in biological chemistry from the University of Minnesota, Twin Cities, and completed postdoctoral training at Harvard University’s Department of Molecular and Cellular Biology. He received a B.Sc. degree in organic chemistry from the University of Barcelona in Spain.
Wilson KM, Mathews-Griner LA, Williamson T, Guha R, Chen L, Shinn P, McKnight C, Michael S, Klumpp-Thomas C, Binder ZA, Ferrer M, Gallia GL, Thomas CJ, Riggins GJ.
SLAS Technol. 2019 Feb;24(1):28-40. doi: 10.1177/2472630318803749. Epub 2018 Oct 5.
Real Time Coverage and eProceedings of Presentations on 9/19-9/21 @CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
Curator: Aviva Lev-Ari, PhD, RN
2.1.5.11 Real Time Coverage and eProceedings of Presentations on 9/19-9/21 @CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair
LIVE 9/19 8AM – 10AM USING CRISPR/Cas9 FOR FUNCTIONAL SCREENING at CHI’s 2nd Annual Symposium CRISPR: Mechanisms and Applications @CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
LIVE 9/19 1:40 – 3:20 EMERGING APPLICATIONS OF CRISPR/CAS9 at CHI’s 2nd Annual Symposium CRISPR: Mechanisms and Applications @ CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
LIVE 9/20 2PM to 5:30PM New Viruses for Therapeutic Gene Delivery at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
LIVE 9/21 8AM to 10:55 AM Expoloring the Versatility of CRISPR/Cas9 at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
LIVE 9/21 8AM to 2:40PM Targeting Cardio-Metabolic Diseases: A focus on Liver Fibrosis and NASH Targets at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
LIVE 9/21 3:20PM to 6:40PM KINASE INHIBITORS FOR CANCER IMMUNOTHERAPY COMBINATIONS & KINASE INHIBITORS FOR AUTOIMMUNE AND INFLAMMATORY DISEASES at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston
GE Healthcare has acquired Biosafe Group SA, a supplier of Integrated Cell Bioprocessing Systems for Cell Therapy and Regenerative Medicine Industry
Reporter and Curator: Dr. Sudipta Saha, Ph.D.
Researchers of University of Texas at San Antonio, USA, have developed a new, non-invasive method which can kill cancer cells in two hours, an advance that may significantly help people with inoperable or hard-to-reach tumours, as well as young children stricken with the deadly disease.
The method involves injecting a chemical compound, nitrobenzaldehyde, into the tumour and allowing it to diffuse into the tissue. A beam of light is then aimed at the tissue, causing the cells to become very acidic inside and, essentially, commit suicide. Within two hours, up to 95 per cent of the targeted cancer cells are estimated to be dead.
The method was tested against triple negative breast cancer, one of the most aggressive types of cancer and one of the hardest to treat. The prognosis for triple negative breast cancer is usually very poor. One treatment in the laboratory was able to stop the tumour from growing and doubled the chances of survival in the mice.
According to the researchers all forms of cancer attempt to make cells acidic on the outside and attract the attention of blood vessels as an attempt to get rid of the acid. But, instead, the cancer cells latches onto the blood vessel and uses it to make the tumour grow bigger.
Chemotherapy treatments target all cells in the body, and certain chemotherapeutics try to keep cancer cells acidic as a way to kill the cancer. This is what causes many cancer patients to lose their hair and become weak. This method however, is more precise and can target just the tumour.
This research is presently extended on drug-resistant cancer cells to make this therapy as strong as possible. The researchers also started to develop a nanoparticle that can be injected into the body to target metastasised cancer cells. The nanoparticle is activated with a wavelength of light which can pass harmlessly through skin, flesh and bone and still activate the nanoparticle.
This non-invasive method will help cancer patients with tumours in areas that have proven problematic for surgeons, such as the brain stem, aorta or spine. It could also help people who have received the maximum amount of radiation treatment and can no longer cope with the scarring and pain that goes along with it, or children who are at risk of developing mutations from radiation as they grow older.
Nuha Buchanan Kadri, Matthew Gdovin, Nizar Alyassin, Justin Avila, Aryana Cruz, Louis Cruz, Steve Holliday, Zachary Jordan, Cameron Ruiz and Jennifer Watts. Photodynamic acidification therapy to reduce triple negative breast cancer growth in vivo. Journal of Clinical Oncology, Vol 34, No 15_suppl (May 20 Supplement), 2016: e12574.
CHICAGO — A new class of cancer immunotherapies, led by pembrolizumab (Keytruda), has taken the oncology world by storm. But with this novel type of treatment comes a new challenge.
The Association of Community Cancer Centers (ACCC) wants to ensure that non-oncologist physicians know how to take care of their patients receiving these agents since doctors in other specialties may not be aware of the side effects related to the immunotherapies.
The initiative is one of the steps taken by the association’s Institute of Clinical Immuno-Oncology’s (ICLIO) in making immunotherapy available in the community.
ICLIO was launched 1 year ago to help prepare community cancer teams and centers to deal with the clinical, coverage, and reimbursement issues related to immunotherapy.
During the American Society of Clinical Oncology annual meeting here MedPage Todayspoke with ACCC President Jennie R. Crews, MD, and ICLIO Chair Lee S. Schwartzberg, MD, about the institute’s growth and future plans.
Schwartzberg, chief of the division of hematology and oncology at the University of Tennessee, as well as executive director of the West Cancer Center in Memphis, said that the field of immunotherapy “is moving so fast that we can’t have enough education.”
“Needs change over time and last year many cancer practices became familiar with immuno-oncology and now we have to go deeper and broader.”
The broadening, he explained, involves educating other medical subspecialists about immune-related toxicities from the new agents.
“The problem is that we see related toxicities that are not managed well, and we’re having trouble with this.”
He cited as two primary examples toxic side effects such as colitis and pneumonitis and the necessity of educating gastroenterologists and pulmonologists about their relationship to immunotherapy.
Many times these subspecialists, as well as dermatologists, endocrinologists, emergency physicians, and internists see autoimmune-related toxicities and first think they are from chemotherapy or infection, according to Schwartzberg.
“But they are going to be going down a very bad path with these patients if they think this way,” noting that a colleague from a leading cancer center had recently mentioned that the institution’s emergency room staff didn’t always understand about immunotherapy reactions.
He said that, although ICLIO does not have direct access to reaching many other subspecialists, it was beginning to develop educational materials that oncologists could share with other medical colleagues, as well as to work with some of the subspecialty societies.
“Education, however, has to be across the board, and has to include patients as well,” he said, adding that many cancer immunotherapy patients were being provided with cards that explained their immunotherapy and could be handed to nurses and physicians at the outset of their medical intervention, saving time and the risk of undergoing the wrong treatment.
In a separate interview, Crews, medical director for Cancer Services PeaceHealth at St. Joseph Medical Center in Bellingham, Wash., said that ACCC members include both academic centers and community practices including both hospital-based and private. (An ACCC public relations representative monitored the interview.)
“We are not focused on what the science is, but rather on how do we take this technology out to the community to bring cancer to where patients are,” she said, adding that she and others are very passionate in the belief that cancer care should be delivered wherever cancer patients live.
She said since ICLIO started in June 2015, much of its infrastructure and programs have been established, including a webinar series, eNewsletters, eLearning Modules, tumor subcommittee working groups, an on-site preceptorship program, an ICLIO stakeholder summit, and an upcoming second national conference this fall in Philadelphia.
That conference will be preceded by a stakeholder summit bringing together providers, patient advocates, payers, pharmaceutical producers, and others, which the ACCC hopes will produce a white paper.
The last year has seen the growth of the initiative’s Scholars Program to about 50 oncologists who have received training through ICLIO’s learning modules.
These scholars will in turn eventually be able to serve as mentors to the 2,000 cancer programs with some 20,000 individual members that make up ACCC’s membership.
Crews said that to date about 700 cancer programs involving some 1,900 individuals have participated in the webinars, and about 100 people attended ICLIO’s first annual conference last October.
She said that in addition to the charitable contribution initially made by Bristol-Myers Squibb last year to help launch ICLIO, Merck has also provided an educational grant, but she would not disclose the amount of the funding.
Most drugs have the chemical composition of light chemical elements, C, H, N, O, S in such combination that determines a unique molecular structures for a given molecular weight value. It is interesting that drug structures include chiral handedness which plays an important role in therapeutics.
Drugs development went in advanced stages in which the therapeutic effects can be predicted and matched with any disease before it is made. However, the science of matching a drug to a curable disease is pretty much a pragmatic activity that is based on trials and observations. The medical trails are needed as a safe method before the drug is released to the public. Drug’s structures, and their fragments are discusses in here.
An interesting example of drug chirality effects on human living cells is Ethambutol, which exists in two chiral forms, the (S,S)-(+)-enantiomer that is used to treat tuberculosis, and the (R,R)-(–)-ethambutol that causes blindness, a significant side effect [1] .
The picture below shows the two enantiomers of Ethambutol, L and D forms, adapted to illustrate the mirror symmetry on a plan placed between the two molecules.
Examples of other enantiomers with important action effects on human body is abundant in literature. For example enantiomers of a chiral drug have identical physical and chemical properties in an achiral environment. In a chiral environment, one enantiomer may display different chemical and pharmacological behavior than the other enantiomer. Because living systems are themselves chiral, each of the enantiomers of a chiral drug can behave very differently in vivo. In other words, the R-enantiomer of a drug will not necessarily behave the same way as the S-enantiomer of the same drug when taken by a patient. For a given chiral drug, it is appropriate to consider the 2 enantiomers as 2 separate drugs with different properties unless proven otherwise.
The increasing availability of single-enantiomer drugs promises to provide clinicians with safer, better-tolerated, and more efficacious medications for treating patients. It is incumbent upon the practicing physician to be familiar with the basic characteristics of chiral pharmaceuticals discussed in this article. In particular, each enantiomer of a given chiral drug may have its own particular pharmacological profile, and a single-enantiomer formulation of a drug may possess different properties than the racemic formulation of the same drug. When both a single-enantiomer and a racemic formulation of a drug are available, the information from clinical trials and clinical experience should be used to decide which formulation is most appropriate.
[1] Padmanabhan, Deepak. “A review of drug isomerism and its significance”. US National Library of Medicine National Institutes of Health. pp. 16–18. doi:10.4103/2229-516X.112233. Retrieved 16 April 2016.
Once upon a time, Merck was looking to candidate omarigliptin—a once-weekly DPP-4 diabetes med—to build up declining sales of its Januvia/Janumet franchise.
But no more. Late last week, the pharma giant quietly announced that it had dropped the Phase III prospect it once regarded as a key cog in its diabetes plans.
So why the change of heart? A new report from healthcare analytics firm Advera Health Analytics found that the weekly therapy came along with more serious side effects than Januvia in two studies. Omarigliptin turned up higher rates of prostate cancer and cardiovascular and hepatobiliary issues, or problems with the liver, pancreas or digestive system, it found. And that kind of profile could have made the drug a hard sell.
Merck says the decision didn’t result from any safety or efficacy concerns. Instead, it may have taken a look at the diabetes landscape and seen a difficult future for the DPP-4 contender.
Such a conclusion would come as no surprise, considering recent developments in the diabetes world. Last year, SGLT2 med Jardiance from Eli Lilly and Boehringer Ingelheim made headlines when it became the first diabetes med to cut down on the combined risk of heart attack, stroke and cardiovascular-related death. Last month, GLP-1 product Victoza from Novo Nordisk accomplished the same feat. And those outcomes leave DPP-4s—which have shown that they don’t increase the risk of serious cardiovascular events, but don’t reduce it, either—out in the cold.
And omarigliptin’s once-weekly advantage may not have done enough to change that, considering the long-acting GLP-1 options out there. Eli Lilly is already marketing once-weekly Trulicity, and Novo is in Phase III with its own long-lasting GLP-1, semaglutide.
But that’s not to say Merck will be left in the dust. With omarigliptin off its hands, the company plans to double down on its pipeline efforts, which include ertugliflozin–an SGLT2 prospect of its own.
Imaging of Cancer Cells, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)
Imaging of Cancer Cells
Larry H. Bernstein, MD, FCAP, Curator
LPBI
Microscope uses nanosecond-speed laser and deep learning to detect cancer cells more efficiently
April 13, 2016
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.
In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
Time-stretch quantitative phase imaging (TS-QPI) and analytics system
The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one.
The new technique combines two components that were invented at UCLA:
A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.
A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.
The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.
The research was supported by NantWorks, LLC.
Abstract of Deep Learning in Label-free Cell Classification
Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.
references:
Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang, Kayvan Reza Niazi & Bahram Jalali. Deep Learning in Label-free Cell Classification. Scientific Reports 6, Article number: 21471 (2016); doi:10.1038/srep21471 (open access)
Supplementary Information
Deep Learning in Label-free Cell Classification
Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang,Kayvan Reza Niazi & Bahram Jalali
Deep learning extracts patterns and knowledge from rich multidimenstional datasets. While it is extensively used for image recognition and speech processing, its application to label-free classification of cells has not been exploited. Flow cytometry is a powerful tool for large-scale cell analysis due to its ability to measure anisotropic elastic light scattering of millions of individual cells as well as emission of fluorescent labels conjugated to cells1,2. However, each cell is represented with single values per detection channels (forward scatter, side scatter, and emission bands) and often requires labeling with specific biomarkers for acceptable classification accuracy1,3. Imaging flow cytometry4,5 on the other hand captures images of cells, revealing significantly more information about the cells. For example, it can distinguish clusters and debris that would otherwise result in false positive identification in a conventional flow cytometer based on light scattering6.
In addition to classification accuracy, the throughput is another critical specification of a flow cytometer. Indeed high throughput, typically 100,000 cells per second, is needed to screen a large enough cell population to find rare abnormal cells that are indicative of early stage diseases. However there is a fundamental trade-off between throughput and accuracy in any measurement system7,8. For example, imaging flow cytometers face a throughput limit imposed by the speed of the CCD or the CMOS cameras, a number that is approximately 2000 cells/s for present systems9. Higher flow rates lead to blurred cell images due to the finite camera shutter speed. Many applications of flow analyzers such as cancer diagnostics, drug discovery, biofuel development, and emulsion characterization require classification of large sample sizes with a high-degree of statistical accuracy10. This has fueled research into alternative optical diagnostic techniques for characterization of cells and particles in flow.
Recently, our group has developed a label-free imaging flow-cytometry technique based on coherent optical implementation of the photonic time stretch concept11. This instrument overcomes the trade-off between sensitivity and speed by using Amplified Time-stretch Dispersive Fourier Transform12,13,14,15. In time stretched imaging16, the object’s spatial information is encoded in the spectrum of laser pulses within a pulse duration of sub-nanoseconds (Fig. 1). Each pulse representing one frame of the camera is then stretched in time so that it can be digitized in real-time by an electronic analog-to-digital converter (ADC). The ultra-fast pulse illumination freezes the motion of high-speed cells or particles in flow to achieve blur-free imaging. Detection sensitivity is challenged by the low number of photons collected during the ultra-short shutter time (optical pulse width) and the drop in the peak optical power resulting from the time stretch. These issues are solved in time stretch imaging by implementing a low noise-figure Raman amplifier within the dispersive device that performs time stretching8,11,16. Moreover, warped stretch transform17,18can be used in time stretch imaging to achieve optical image compression and nonuniform spatial resolution over the field-of-view19. In the coherent version of the instrument, the time stretch imaging is combined with spectral interferometry to measure quantitative phase and intensity images in real-time and at high throughput20. Integrated with a microfluidic channel, coherent time stretch imaging system in this work measures both quantitative optical phase shift and loss of individual cells as a high-speed imaging flow cytometer, capturing 36 million images per second in flow rates as high as 10 meters per second, reaching up to 100,000 cells per second throughput.
Box 1: The pulse train is spatially dispersed into a train of rainbow flashes illuminating the target as line scans. The spatial features of the target are encoded into the spectrum of the broadband optical pulses, each representing a one-dimensional frame. The ultra-short optical pulse illumination freezes the motion of cells during high speed flow to achieve blur-free imaging with a throughput of 100,000 cells/s. The phase shift and intensity loss at each location within the field of view are embedded into the spectral interference patterns using a Michelson interferometer. Box 2: The interferogram pulses were then stretched in time so that spatial information could be mapped into time through time-stretch dispersive Fourier transform (TS-DFT), and then captured by a single pixel photodetector and an analog-to-digital converter (ADC). The loss of sensitivity at high shutter speed is compensated by stimulated Raman amplification during time stretch. Box 3: (a) Pulse synchronization; the time-domain signal carrying serially captured rainbow pulses is transformed into a series of one-dimensional spatial maps, which are used for forming line images. (b) The biomass density of a cell leads to a spatially varying optical phase shift. When a rainbow flash passes through the cells, the changes in refractive index at different locations will cause phase walk-off at interrogation wavelengths. Hilbert transformation and phase unwrapping are used to extract the spatial phase shift. (c) Decoding the phase shift in each pulse at each wavelength and remapping it into a pixel reveals the protein concentration distribution within cells. The optical loss induced by the cells, embedded in the pulse intensity variations, is obtained from the amplitude of the slowly varying envelope of the spectral interferograms. Thus, quantitative optical phase shift and intensity loss images are captured simultaneously. Both images are calibrated based on the regions where the cells are absent. Cell features describing morphology, granularity, biomass, etc are extracted from the images. (d) These biophysical features are used in a machine learning algorithm for high-accuracy label-free classification of the cells.
On another note, surface markers used to label cells, such as EpCAM21, are unavailable in some applications; for example, melanoma or pancreatic circulating tumor cells (CTCs) as well as some cancer stem cells are EpCAM-negative and will escape EpCAM-based detection platforms22. Furthermore, large-population cell sorting opens the doors to downstream operations, where the negative impacts of labels on cellular behavior and viability are often unacceptable23. Cell labels may cause activating/inhibitory signal transduction, altering the behavior of the desired cellular subtypes, potentially leading to errors in downstream analysis, such as DNA sequencing and subpopulation regrowth. In this way, quantitative phase imaging (QPI) methods24,25,26,27 that categorize unlabeled living cells with high accuracy are needed. Coherent time stretch imaging is a method that enables quantitative phase imaging at ultrahigh throughput for non-invasive label-free screening of large number of cells.
In this work, the information of quantitative optical loss and phase images are fused into expert designed features, leading to a record label-free classification accuracy when combined with deep learning. Image mining techniques are applied, for the first time, to time stretch quantitative phase imaging to measure biophysical attributes including protein concentration, optical loss, and morphological features of single cells at an ultrahigh flow rate and in a label-free fashion. These attributes differ widely28,29,30,31 among cells and their variations reflect important information of genotypes and physiological stimuli32. The multiplexed biophysical features thus lead to information-rich hyper-dimensional representation of the cells for label-free classification with high statistical precision.
We further improved the accuracy, repeatability, and the balance between sensitivity and specificity of our label-free cell classification by a novel machine learning pipeline, which harnesses the advantages of multivariate supervised learning, as well as unique training by evolutionary global optimization of receiver operating characteristics (ROC). To demonstrate sensitivity, specificity, and accuracy of multi-feature label-free flow cytometry using our technique, we classified (1) OT-IIhybridoma T-lymphocytes and SW-480 colon cancer epithelial cells, and (2) Chlamydomonas reinhardtii algal cells (herein referred to as Chlamydomonas) based on their lipid content, which is related to the yield in biofuel production. Our preliminary results show that compared to classification by individual biophysical parameters, our label-free hyperdimensional technique improves the detection accuracy from 77.8% to 95.5%, or in other words, reduces the classification inaccuracy by about five times. ……..
Feature Extraction
The decomposed components of sequential line scans form pairs of spatial maps, namely, optical phase and loss images as shown in Fig. 2 (see Section Methods: Image Reconstruction). These images are used to obtain biophysical fingerprints of the cells8,36. With domain expertise, raw images are fused and transformed into a suitable set of biophysical features, listed in Table 1, which the deep learning model further converts into learned features for improved classification.
The new technique combines two components that were invented at UCLA:
A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.
A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.
The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.
The optical loss images of the cells are affected by the attenuation of multiplexed wavelength components passing through the cells. The attenuation itself is governed by the absorption of the light in cells as well as the scattering from the surface of the cells and from the internal cell organelles. The optical loss image is derived from the low frequency component of the pulse interferograms. The optical phase image is extracted from the analytic form of the high frequency component of the pulse interferograms using Hilbert Transformation, followed by a phase unwrapping algorithm. Details of these derivations can be found in Section Methods. Also, supplementary Videos 1 and 2 show measurements of cell-induced optical path length difference by TS-QPI at four different points along the rainbow for OT-II and SW-480, respectively.
Table 1: List of extracted features.
Feature Name Description Category
Figure 3: Biophysical features formed by image fusion.
(a) Pairwise correlation matrix visualized as a heat map. The map depicts the correlation between all major 16 features extracted from the quantitative images. Diagonal elements of the matrix represent correlation of each parameter with itself, i.e. the autocorrelation. The subsets in box 1, box 2, and box 3 show high correlation because they are mainly related to morphological, optical phase, and optical loss feature categories, respectively. (b) Ranking of biophysical features based on their AUCs in single-feature classification. Blue bars show performance of the morphological parameters, which includes diameter along the interrogation rainbow, diameter along the flow direction, tight cell area, loose cell area, perimeter, circularity, major axis length, orientation, and median radius. As expected, morphology contains most information, but other biophysical features can contribute to improved performance of label-free cell classification. Orange bars show optical phase shift features i.e. optical path length differences and refractive index difference. Green bars show optical loss features representing scattering and absorption by the cell. The best performed feature in these three categories are marked in red.
Figure 4: Machine learning pipeline. Information of quantitative optical phase and loss images are fused to extract multivariate biophysical features of each cell, which are fed into a fully-connected neural network.
The neural network maps input features by a chain of weighted sum and nonlinear activation functions into learned feature space, convenient for classification. This deep neural network is globally trained via area under the curve (AUC) of the receiver operating characteristics (ROC). Each ROC curve corresponds to a set of weights for connections to an output node, generated by scanning the weight of the bias node. The training process maximizes AUC, pushing the ROC curve toward the upper left corner, which means improved sensitivity and specificity in classification.
…. How to cite this article: Chen, C. L. et al. Deep Learning in Label-free Cell Classification.
To better characterize the functional context of genomic variations in cancer, researchers developed a new computer algorithm called REVEALER. [UC San Diego Health]
Scientists at the University of California San Diego School of Medicine and the Broad Institute say they have developed a new computer algorithm—REVEALER—to better characterize the functional context of genomic variations in cancer. The tool, described in a paper (“Characterizing Genomic Alterations in Cancer by Complementary Functional Associations”) published in Nature Biotechnology, is designed to help researchers identify groups of genetic variations that together associate with a particular way cancer cells get activated, or how they respond to certain treatments.
REVEALER is available for free to the global scientific community via the bioinformatics software portal GenePattern.org.
“This computational analysis method effectively uncovers the functional context of genomic alterations, such as gene mutations, amplifications, or deletions, that drive tumor formation,” said senior author Pablo Tamayo, Ph.D., professor and co-director of the UC San Diego Moores Cancer Center Genomics and Computational Biology Shared Resource.
Dr. Tamayo and team tested REVEALER using The Cancer Genome Atlas (TCGA), the NIH’s database of genomic information from more than 500 human tumors representing many cancer types. REVEALER revealed gene alterations associated with the activation of several cellular processes known to play a role in tumor development and response to certain drugs. Some of these gene mutations were already known, but others were new.
For example, the researchers discovered new activating genomic abnormalities for beta-catenin, a cancer-promoting protein, and for the oxidative stress response that some cancers hijack to increase their viability.
REVEALER requires as input high-quality genomic data and a significant number of cancer samples, which can be a challenge, according to Dr. Tamayo. But REVEALER is more sensitive at detecting similarities between different types of genomic features and less dependent on simplifying statistical assumptions, compared to other methods, he adds.
“This study demonstrates the potential of combining functional profiling of cells with the characterizations of cancer genomes via next-generation sequencing,” said co-senior author Jill P. Mesirov, Ph.D., professor and associate vice chancellor for computational health sciences at UC San Diego School of Medicine.
Characterizing genomic alterations in cancer by complementary functional associations
Jong Wook Kim, Olga B Botvinnik, Omar Abudayyeh, Chet Birger, et al.
Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes
Figure 2: REVEALER results for transcriptional activation of β-catenin in cancer.close
(a) This heatmap illustrates the use of the REVEALER approach to find complementary genomic alterations that match the transcriptional activation of β-catenin in cancer. The target profile is a TCF4 reporter that provides an estimate of…
An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models
Jonathan P. Celli, Imran Rizvi, Adam R. Blanden, Iqbal Massodi, Michael D. Glidden, Brian W. Pogue & Tayyaba Hasan
While it is increasingly recognized that three-dimensional (3D) cell culture models recapitulate drug responses of human cancers with more fidelity than monolayer cultures, a lack of quantitative analysis methods limit their implementation for reliable and routine assessment of emerging therapies. Here, we introduce an approach based on computational analysis of fluorescence image data to provide high-content readouts of dose-dependent cytotoxicity, growth inhibition, treatment-induced architectural changes and size-dependent response in 3D tumour models. We demonstrate this approach in adherent 3D ovarian and pancreatic multiwell extracellular matrix tumour overlays subjected to a panel of clinically relevant cytotoxic modalities and appropriately designed controls for reliable quantification of fluorescence signal. This streamlined methodology reads out the high density of information embedded in 3D culture systems, while maintaining a level of speed and efficiency traditionally achieved with global colorimetric reporters in order to facilitate broader implementation of 3D tumour models in therapeutic screening.
The attrition rates for preclinical development of oncology therapeutics are particularly dismal due to a complex set of factors which includes 1) the failure of pre-clinical models to recapitulate determinants of in vivo treatment response, and 2) the limited ability of available assays to extract treatment-specific data integral to the complexities of therapeutic responses1,2,3. Three-dimensional (3D) tumour models have been shown to restore crucial stromal interactions which are missing in the more commonly used 2D cell culture and that influence tumour organization and architecture4,5,6,7,8, as well as therapeutic response9,10, multicellular resistance (MCR)11,12, drug penetration13,14, hypoxia15,16, and anti-apoptotic signaling17. However, such sophisticated models can only have an impact on therapeutic guidance if they are accompanied by robust quantitative assays, not only for cell viability but also for providing mechanistic insights related to the outcomes. While numerous assays for drug discovery exist18, they are generally not developed for use in 3D systems and are often inherently unsuitable. For example, colorimetric conversion products have been noted to bind to extracellular matrix (ECM)19 and traditional colorimetric cytotoxicity assays reduce treatment response to a single number reflecting a biochemical event that has been equated to cell viability (e.g. tetrazolium salt conversion20). Such approaches fail to provide insight into the spatial patterns of response within colonies, morphological or structural effects of drug response, or how overall culture viability may be obscuring the status of sub-populations that are resistant or partially responsive. Hence, the full benefit of implementing 3D tumour models in therapeutic development has yet to be realized for lack of analytical methods that describe the very aspects of treatment outcome that these systems restore.
Motivated by these factors, we introduce a new platform for quantitative in situ treatment assessment (qVISTA) in 3D tumour models based on computational analysis of information-dense biological image datasets (bioimage-informatics)21,22. This methodology provides software end-users with multiple levels of complexity in output content, from rapidly-interpreted dose response relationships to higher content quantitative insights into treatment-dependent architectural changes, spatial patterns of cytotoxicity within fields of multicellular structures, and statistical analysis of nodule-by-nodule size-dependent viability. The approach introduced here is cognizant of tradeoffs between optical resolution, data sampling (statistics), depth of field, and widespread usability (instrumentation requirement). Specifically, it is optimized for interpretation of fluorescent signals for disease-specific 3D tumour micronodules that are sufficiently small that thousands can be imaged simultaneously with little or no optical bias from widefield integration of signal along the optical axis of each object. At the core of our methodology is the premise that the copious numerical readouts gleaned from segmentation and interpretation of fluorescence signals in these image datasets can be converted into usable information to classify treatment effects comprehensively, without sacrificing the throughput of traditional screening approaches. It is hoped that this comprehensive treatment-assessment methodology will have significant impact in facilitating more sophisticated implementation of 3D cell culture models in preclinical screening by providing a level of content and biological relevance impossible with existing assays in monolayer cell culture in order to focus therapeutic targets and strategies before costly and tedious testing in animal models.
Using two different cell lines and as depicted in Figure 1, we adopt an ECM overlay method pioneered originally for 3D breast cancer models23, and developed in previous studies by us to model micrometastatic ovarian cancer19,24. This system leads to the formation of adherent multicellular 3D acini in approximately the same focal plane atop a laminin-rich ECM bed, implemented here in glass-bottom multiwell imaging plates for automated microscopy. The 3D nodules resultant from restoration of ECM signaling5,8, are heterogeneous in size24, in contrast to other 3D spheroid methods, such as rotary or hanging drop cultures10, in which cells are driven to aggregate into uniformly sized spheroids due to lack of an appropriate substrate to adhere to. Although the latter processes are also biologically relevant, it is the adherent tumour populations characteristic of advanced metastatic disease that are more likely to be managed with medical oncology, which are the focus of therapeutic evaluation herein. The heterogeneity in 3D structures formed via ECM overlay is validated here by endoscopic imaging ofin vivo tumours in orthotopic xenografts derived from the same cells (OVCAR-5).
Figure 1: A simplified schematic flow chart of imaging-based quantitative in situ treatment assessment (qVISTA) in 3D cell culture.
(This figure was prepared in Adobe Illustrator® software by MD Glidden, JP Celli and I Rizvi). A detailed breakdown of the image processing (Step 4) is provided in Supplemental Figure 1.
A critical component of the imaging-based strategy introduced here is the rational tradeoff of image-acquisition parameters for field of view, depth of field and optical resolution, and the development of image processing routines for appropriate removal of background, scaling of fluorescence signals from more than one channel and reliable segmentation of nodules. In order to obtain depth-resolved 3D structures for each nodule at sub-micron lateral resolution using a laser-scanning confocal system, it would require ~ 40 hours (at approximately 100 fields for each well with a 20× objective, times 1 minute/field for a coarse z-stack, times 24 wells) to image a single plate with the same coverage achieved in this study. Even if the resources were available to devote to such time-intensive image acquisition, not to mention the processing, the optical properties of the fluorophores would change during the required time frame for image acquisition, even with environmental controls to maintain culture viability during such extended imaging. The approach developed here, with a mind toward adaptation into high throughput screening, provides a rational balance of speed, requiring less than 30 minutes/plate, and statistical rigour, providing images of thousands of nodules in this time, as required for the high-content analysis developed in this study. These parameters can be further optimized for specific scenarios. For example, we obtain the same number of images in a 96 well plate as for a 24 well plate by acquiring only a single field from each well, rather than 4 stitched fields. This quadruples the number conditions assayed in a single run, at the expense of the number of nodules per condition, and therefore the ability to obtain statistical data sets for size-dependent response, Dfrac and other segmentation-dependent numerical readouts.
We envision that the system for high-content interrogation of therapeutic response in 3D cell culture could have widespread impact in multiple arenas from basic research to large scale drug development campaigns. As such, the treatment assessment methodology presented here does not require extraordinary optical instrumentation or computational resources, making it widely accessible to any research laboratory with an inverted fluorescence microscope and modestly equipped personal computer. And although we have focused here on cancer models, the methodology is broadly applicable to quantitative evaluation of other tissue models in regenerative medicine and tissue engineering. While this analysis toolbox could have impact in facilitating the implementation of in vitro 3D models in preclinical treatment evaluation in smaller academic laboratories, it could also be adopted as part of the screening pipeline in large pharma settings. With the implementation of appropriate temperature controls to handle basement membranes in current robotic liquid handling systems, our analyses could be used in ultra high-throughput screening. In addition to removing non-efficacious potential candidate drugs earlier in the pipeline, this approach could also yield the additional economic advantage of minimizing the use of costly time-intensive animal models through better estimates of dose range, sequence and schedule for combination regimens.
Microscope Uses AI to Find Cancer Cells More Efficiently
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.
In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses.
There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one. It combines two components that were invented at UCLA: a photonic time stretch microscope, which is capable of quickly imaging cells in blood samples, and a deep learning computer program that identifies cancer cells with over 95 percent accuracy.
Deep learning is a form of artificial intelligence that uses complex algorithms to extract meaning from data with the goal of achieving accurate decision making.
The study, which was published in the journal Nature Scientific Reports, was led by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering; Claire Lifan Chen, a UCLA doctoral student; and Ata Mahjoubfar, a UCLA postdoctoral fellow.
Photonic time stretch was invented by Jalali, and he holds a patent for the technology. The new microscope is just one of many possible applications; it works by taking pictures of flowing blood cells using laser bursts in the way that a camera uses a flash. This process happens so quickly — in nanoseconds, or billionths of a second — that the images would be too weak to be detected and too fast to be digitized by normal instrumentation.
The new microscope overcomes those challenges using specially designed optics that boost the clarity of the images and simultaneously slow them enough to be detected and digitized at a rate of 36 million images per second. It then uses deep learning to distinguish cancer cells from healthy white blood cells.
“Each frame is slowed down in time and optically amplified so it can be digitized,” Mahjoubfar said. “This lets us perform fast cell imaging that the artificial intelligence component can distinguish.”
Normally, taking pictures in such minuscule periods of time would require intense illumination, which could destroy live cells. The UCLA approach also eliminates that problem.
“The photonic time stretch technique allows us to identify rogue cells in a short time with low-level illumination,” Chen said.
The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease. ….. see also http://www.nature.com/article-assets/npg/srep/2016/160315/srep21471/images_hires/m685/srep21471-f1.jpg
References in 
2012pharmaceutical
Amandeep Kaur
Aashir Awan, Phd
Abhisar Anand
Adina Hazan
Alan F. Kaul, PharmD., MS, MBA, FCCP
alexcrystal6
anamikasarkar
apreconasia
aviralvatsa
David Orchard-Webb, PhD
danutdaagmailcom
Demet Sag, Ph.D., CRA, GCP
Dror Nir
dsmolyar
Ethan Coomber
evelinacohn
Gail S Thornton
Irina Robu
jayzmit48
jdpmd
jshertok
kellyperlman
Ed Kislauskis
larryhbern
Madison Davis
marzankhan
megbaker58
ofermar2020
Dr. Pati
pkandala
ritusaxena
Rick Mandahl
sjwilliamspa
Srinivas Sriram
stuartlpbi
Dr. Sudipta Saha
tildabarliya
vaishnavee24
zraviv06
zs22
