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Live Conference Coverage @Medcitynews Converge 2018 @Philadelphia: Promising Drugs and Breaking Down Silos

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Prevention: Research & Programs, Clinical & Translational, Disease Biology, Small Molecules in Development of Therapeutic Drugs, FDA Regulatory Affairs, Health Economics and Outcomes Research, Pharmaceutical Discovery, Pharmaceutical Drug Discovery, Pharmaceutical Industry Competitive Intelligence, Uncategorized, Value-based Drug Pricing, tagged @science 2_0, anti-cancer drugs, Big data, cancer cost, cost benefit, Data analysis, data sharing, DNASeq Data Analysis, drug costs, health outcomes, ICER, insurers, Keytruda, Keytruda (pembrolizumab), managing cost and quality, medical information, Medicare, medicare costs, merck, Open access, Pfizer, pharma industry, Pharmaceutical, Quality of life, science communication on July 12, 2018| Leave a Comment »

Live Conference Coverage @Medcitynews Converge 2018 @Philadelphia: Promising Drugs and Breaking Down Silos

Reporter: Stephen J. Williams, PhD

Promising Drugs, Pricing and Access

The drug pricing debate rages on. What are the solutions to continuing to foster research and innovation, while ensuring access and affordability for patients? Can biosimilars and generics be able to expand market access in the U.S.?

Moderator: Bunny Ellerin, Director, Healthcare and Pharmaceutical Management Program, Columbia Business School
Speakers:
Patrick Davish, AVP, Global & US Pricing/Market Access, Merck
Robert Dubois M.D., Chief Science Officer and Executive Vice President, National Pharmaceutical Council
Gary Kurzman, M.D., Senior Vice President and Managing Director, Healthcare, Safeguard Scientifics
Steven Lucio, Associate Vice President, Pharmacy Services, Vizient

What is working and what needs to change in pricing models?

Robert: He sees so many players in the onStevencology space discovering new drugs and other drugs are going generic (that is what is working). However are we spending too much on cancer care relative to other diseases (their initiative Going Beyond the Surface)

Steven: the advent of biosimilars is good for the industry

Patrick: large effort in oncology, maybe too much (750 trials on Keytruda) and he says pharma is spending on R&D (however clinical trials take large chunk of this money)

Robert: cancer has gotten a free ride but cost per year relative to benefit looks different than other diseases. Are we overinvesting in cancer or is that a societal decision

Gary: maybe as we become more specific with precision medicines high prices may be a result of our success in specifically targeting a mutation. We need to understand the targeted drugs and outcomes.

Patrick: “Cancer is the last big frontier” but he says prices will come down in most cases. He gives the example of Hep C treatment… the previous only therapeutic option was a very toxic yearlong treatment but the newer drugs may be more cost effective and safer

Steven: Our blockbuster drugs could diffuse the expense but now with precision we can’t diffuse the expense over a large number of patients

President’s Cancer Panel Recommendation

Six recommendations

promoting value based pricing
enabling communications of cost
financial toxicity
stimulate competition biosimilars
value based care
invest in biomedical research

Patrick: the government pricing regime is hurting. Alot of practical barriers but Merck has over 200 studies on cost basis

Robert: many concerns/impetus started in Europe on pricing as they are a set price model (EU won’t pay more than x for a drug). US is moving more to outcomes pricing. For every one health outcome study three studies did not show a benefit. With cancer it is tricky to establish specific health outcomes. Also Medicare gets best price status so needs to be a safe harbor for payers and biggest constraint is regulatory issues.

Steven: They all want value based pricing but we don’t have that yet and there is a challenge to understand the nuances of new therapies. Hard to align all the stakeholders together so until some legislation starts to change the reimbursement-clinic-patient-pharma obstacles. Possibly the big data efforts discussed here may help align each stakeholders goals.

Gary: What is the data necessary to understand what is happening to patients and until we have that information it still will be complicated to determine where investors in health care stand at in this discussion

Robert: on an ICER methods advisory board: 1) great concern of costs how do we determine fair value of drug 2) ICER is only game in town, other orgs only give recommendations 3) ICER evaluates long term value (cost per quality year of life), budget impact (will people go bankrupt)

4) ICER getting traction in the public eye and advocates 5) the problem is ICER not ready for prime time as evidence keeps changing or are they keeping the societal factors in mind and they don’t have total transparancy in their methodology

Steven: We need more transparency into all the costs associated with the drug and therapy and value-based outcome. Right now price is more of a black box.

Moderator: pointed to a recent study which showed that outpatient costs are going down while hospital based care cost is going rapidly up (cost of site of care) so we need to figure out how to get people into lower cost setting

Breaking Down Silos in Research

“Silo” is healthcare’s four-letter word. How are researchers, life science companies and others sharing information that can benefit patients more quickly? Hear from experts at institutions that are striving to tear down the walls that prevent data from flowing.

Moderator: Vini Jolly, Executive Director, Woodside Capital Partners
Speakers:
Ardy Arianpour, CEO & Co-Founder, Seqster @seqster
Lauren Becnel, Ph.D., Real World Data Lead for Oncology, Pfizer
Rakesh Mathew, Innovation, Research, & Development Lead, HealthShareExchange
David Nace M.D., Chief Medical Officer, Innovaccer

Seqster: Seqster is a secure platform that helps you and your family manage medical records, DNA, fitness, and nutrition data—all in one place. Founder has a genomic sequencing background but realized sequence information needs to be linked with medical records.

HealthShareExchange.org :

HealthShare Exchange envisions a trusted community of healthcare stakeholders collaborating to deliver better care to consumers in the greater Philadelphia region. HealthShare Exchange will provide secure access to health information to enable preventive and cost-effective care; improve quality of patient care; and facilitate care transitions. They have partnered with multiple players in healthcare field and have data on over 7 million patients.

Innovacer

Data can be overwhelming, but it doesn’t have to be this way. To drive healthcare efficiency, we designed a modular suite of products for a smooth transition into a data-driven world within 4 weeks. Why does it take so much money to move data around and so slowly?

What is interoperatibility?

Ardy: We knew in genomics field how to build algorithms to analyze big data but how do we expand this from a consumer standpoint and see and share your data.

Lauren: how can we use the data between patients, doctors, researchers? On the research side genomics represent only 2% of data. Silos are one issue but figuring out the standards for data (collection, curation, analysis) is not set. Still need to improve semantic interoperability. For example Flatiron had good annotated data on male metastatic breast cancer.

David: Technical interopatabliltiy (platform), semantic interopatability (meaning or word usage), format (syntactic) interopatibility (data structure). There is technical interoperatiblity between health system but some semantic but formats are all different (pharmacies use different systems and write different prescriptions using different suppliers). In any value based contract this problem is a big issue now (we are going to pay you based on the quality of your performance then there is big need to coordinate across platforms). We can solve it by bringing data in real time in one place and use mapping to integrate the format (need quality control) then need to make the data democratized among players.

Rakesh: Patients data should follow the patient. Of Philadelphia’s 12 health systems we had a challenge to make data interoperatable among them so tdhey said to providers don’t use portals and made sure hospitals were sending standardized data. Health care data is complex.

David: 80% of clinical data is noise. For example most eMedical Records are text. Another problem is defining a patient identifier which US does not believe in.

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Immunotherapy Resistance Rears Its Ugly Head: PD-1 Resistant Metastatic Melanoma and More

Posted in Cancer - General, Cancer and Current Therapeutics, tagged Cancer immunology, cancer immunotherapeutics, cancer resistance, Keytruda, malignant melanoma, PD-1, PD-1 inhibitor, Resistance on July 14, 2016| Leave a Comment »

Immunotherapy Resistance Rears Its Ugly Head Again: PD-1 Resistant Metastatic Melanoma and More

Curator/Reporter: Stephen J. Williams, Ph.D.

From GenomeWeb

Source: https://www.genomeweb.com/sequencing/immune-gene-mutations-found-immunotherapy-resistant-metastatic-melanoma-patients?utm_source=SilverpopMailing&utm_medium=email&utm_campaign=Daily%20News:%20U%20of%20Texas%20Southwestern%20Medical%20Center%20Licenses%20Exosome%20Tech%20to%20Peregrine%20Pharmaceuticals%20-%2007/14/2016%2011:05:00%20AM

Immune Gene Mutations Found in Immunotherapy-Resistant Metastatic Melanoma Patients

Jul 14, 2016

Andrea Anderson

NEW YORK (GenomeWeb) – Researchers from the US and the Netherlands reported in the New England Journal of Medicine that they have identified mutations in immune system-related genes in individuals who initially responded to anti-PD-1 treatment for metastatic melanoma treatment, but relapsed after six months or more.

A team led by investigators at the University of California at Los Angeles, the Jonsson Comprehensive Cancer Center, and the Netherlands Cancer Institute did exome sequencing on tumor samples from four individuals with metastatic melanoma prior to treatment with pembrolizumab (marketed as Keytruda by Merck). The researchers also assessed protein-coding sequences in tumor samples taken after late relapse, comparing the baseline and relapse tumors to search for mutations related to checkpoint blockade therapy resistance.

They uncovered suspicious mutations in three of the four individuals. In one individual, for example, they saw a truncating mutation affecting the beta-2-microglobulin (B2M) gene, which contributes to expression of class I major histocompatibility complex molecules recognized by the immune system’s CD8 T cells. Two more relapse tumors contained loss-of-function mutations to JAK1 or JAK2 — genes coding for interferon-related kinase enzymes.

“The mutations make the tumor resistant to the way the immune system tries to kill it,” first author Jesse Zaretsky, an MD/PhD student in senior author Antoni Ribas’ University of California at Los Angeles lab, told GenomeWeb. For example, he explained, the JAK mutations “are associated with the interferon receptor and make the tumors insensitive to the signals the immune system sends to slow [tumor] growth and kill the cancer.”

While roughly three-quarters of individuals treated with anti-PD-1 therapies show durable treatment responses, acquired resistance can occur, even long after immunotherapy-mediated tumor regression.

“With the approval of PD-1 checkpoint blockade agents for the treatment of patients with melanoma, lung cancer, and other cancers, it is anticipated that cases of late relapse after initial response will increase,” the study’s authors wrote. “Understanding the molecular mechanisms of acquired resistance … may open options for the rational design of salvage combination therapies or preventative interventions and may guide mechanistic biomarker studies for the selection of patients, before the initiation of treatment, who are unlikely to have a response.”

The team started with 78 metastatic melanoma patients who were treated with pembrolizumab at UCLA. Of the 42 individuals who showed an objective response to the checkpoint blockade therapy, 15 eventually experienced disease progression.

From that group of 15 patients, the researchers focused on four patients with late-acquired resistance — six months or more after response to pembrolizumab as a single agent — for whom there was sufficient biopsy material and clinical information available. Each of the patients had been receiving continuous doses of the drug until relapse, which occurred after a mean of nearly 21 months.

When the investigators scrutinized biopsies from the relapse tumors, they saw enhanced PD-L1 expression at the edges of tumors, along with CD8 T cells attempting to infiltrate the tumors. After capturing protein-coding portions of the genome in baseline and relapse tumor samples with Nimblegen exome kits, the team sequenced the exomes to nearly 150-fold average coverage using the Illumina HiSeq 2000.

“We wanted to capture all of the mutations down to low allele frequencies to get a picture of everything that was going on in the tumors, both before they went on the treatment and after [the tumors] came back,” Zaretsky said.

In the two cases marked by new JAK1 or JAK2 mutations at relapse, the team found that 93 percent to nearly 96 percent of baseline tumor mutations persisted in the relapse tumors.

The researchers suspect resistance mutations arose from clonal populations in the metastatic tumors that expanded after anti-PD-1 treatment. From allele frequency patterns in the relapsed tumors with JAK1/2 mutations, for example, they concluded that “tumors resistant to anti-PD-1 are a relatively homogeneous population derived directly from the baseline tumor and that acquisition of the JAK mutations was an early founder event.”

Even so, they didn’t detect burgeoning resistance mutations in the pre-pembrolizumab-treatment tumors, Zaretsky said, perhaps because such alterations were present in very few cells in the baseline tumors.

In cell lines established from the individual with JAK2 loss-of-function mutations at relapse, the team’s NanoString Technologies’ nCounter expression experiments pointed to loss of JAK2 protein expression after treatment progression, along with a dip in interferon gamma activity and diminished production of proteins involved in antigen presentation and T cell activity.