Posts Tagged ‘drug discovery’

A Glimpse at Drug Discovery’s Future from H3 Biomedicine CEO Markus Warmuth

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October 5th, 2012
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As many of you know, R&D progress in drug discovery has been a challenge for “big pharma” and biotech firms alike. The costs and risks are enormous, and the rewards are increasingly elusive. For many young firms, the “valley of death” is a very real obstacle as cash burn rates exceed the pace of successful delivery of new drugs to market. What can startups (and larger companies) do? Markus Warmuth, CEO of Cambridge, Massachusetts-based H3 Biomedicine, talked with us about his company’s strategies for giving drug discovery a much-needed boost.

H3 Biomedicine Inc. is a privately held, uniquely structured oncology discovery enterprise. H3 is applying the expertise of leading scientists to the integration of insights from cancer genomics with innovative capabilities in synthetic chemistry and tumor biology to discover patient-based, genomics-driven, small molecule drugs, which represent the most promising current opportunity in cancer therapeutics. H3 Biomedicine will achieve its goals through a unique relationship with the pharmaceutical company Eisai Inc. Eisai has pledged up to $200 million in research funding to H3 Biomedicine, as well as additional support for the clinical development of H3 Biomedicine programs.

Q: What does H3’s drug discovery approach say about the current healthcare economic climate?

Warmuth: Our scientific operation and implementation of strategy is starting at a time when there’s a lot of genomic information becoming available from large numbers of cancer patients. There’s The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). It’s an absolutely fantastic time for drug discovery using a human biology or genome based approach. Now that we have genomic information available through public portals on 5,000 or more patients, we can be very systematic.

For financing, our company is based on a very different model from most companies within the small-sized biotech sector. Because we are funded by Eisai, we are less focused on short-term success and exit strategies. Human biology is very complicated; you can’t resolve issues in 3-5 years – so we are fortunate to have the ability to take a longer term approach to oncology drug discovery.

Q: How does your model let you innovate?

Warmuth: We are looking at a 6- to 8-year trajectory. This gives us time to dig deeply into genomic information, and to create biological hypotheses. On the discovery end, it prepares us to find the right chemicals to address genetic changes. We can take a detailed look at the chemical space and enzyme structure/function, and marry that with human biology. It’s relatively easy to come up with compounds, but we don’t want to ignore the question of whether a particular kinase is biologically relevant—whether an inhibitor of that kinase is more than just an interesting chemical, and whether it actually has a beneficial effect in vivo.

Q: What does it mean to you as CEO to have the luxury to innovate?

Warmuth: It’s key to have the right tools to test the hypothesis. The advantage of genomics data (and access to genomics databases) – the way it is generated by TCGA and ICGC – is that we have consistent, multilayered data from many different patients. We have information on normal tissue but also disease-related RNA sequencing data, which allows us to measure gene expression but also delivers insights into alternative gene splicing, SNP arrays to get into gene copy number changes, and so on. With this, we can start to do some really cool biological networking exercises. We do, however, need to set up new models—cell lines do not enable the same level of analysis as human samples and related genetic analyses.

Q: Why is cancer the preferred disease state for H3?

Warmuth: It’s an obvious starting point. It’s the disease with the most genomic and mechanistic information available at this point, in part because cancer tissue is more accessible than tissue related to other disease areas (compared to neuroscience, for example). Other disease areas may be catching up; there are large-scale SNP genotype and other genomic studies advancing rapidly for many other human diseases. We’re using that genetic and genomic information to drive multiple disease/discovery hypotheses.

Q: I believe that cancer is on the leading edge of drug discovery. Do you agree?

Warmuth: I certainly agree. In the areas of understanding human disease biology, relating to genetic and epigenetic changes, signaling pathways and changes in tissue, cancer is well ahead. If you think about it, cancer is probably the disease where the diseased tissue changes most, compared to normal tissue.

We’ll share more from our discussions with Dr. Warmuth in a future post on new directions in target validation, the value of open-source genomics data, and how H3’s discovery strategy differs from that of big pharma. In the mean time, you can read about H3’s most recent news announcement here.

What do you think of H3’s model? How have advances in genomics affected your product development strategies? Is there a way to digitize this new biological knowledge, or even create tools to help uncover other biological trends? Please share your thoughts with us here.

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Through the Murky Slog: Part II—A New Light for Cancer Therapies?

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November 9th, 2011
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Last week, we discussed new drug approvals that reflected a paradigm shift for cancer drug development and for treatment of people living with cancer. Finally, we are starting to see a matchup of specific diagnostics with targeted biotherapeutics to address (effectively, we hope) targeted treatments for smaller groups of cancer patients.

Just recently, the American Society for Clinical Oncology (ASCO) urged the use of new biological knowledge to develop treatments faster, design more targeted clinical trials, and use information technology to integrate once-separate translational and clinical research. ASCO even says that targeted therapies can improve clinical trial responses from 8 to 30 percent. Also, just recently, the FDA gave itself a pat on the back as it highlighted its recent innovative drug approvals, with targeted cancer therapies included among those on the list.

What both of these events underscore is that we’re now finally seeing real co-development of drugs and companion diagnostics. This is a refreshing departure from the old system in which tests were developed after the drug was approved, often to rescue certain drugs that were facing rejection or had been pulled from the market.

We expect this trend to continue and will probably start to see new tests in two categories—

  1. Tests designed to include or to qualify patients. For example, if the specific drug target is present or activated, say, by a genetic alignment that creates the target (like Bcr-Abl fusion for leukemia), or mutations activate the target (like V600E in BRAF for melanoma), it will be sensitive to inhibitors.
  2. Tests designed to exclude or to disqualify patients. An example would be tests that determine the vicinity of the target pathway to determine if pre-existing mutations would enable the cancer to bypass drug activity (like KRAS mutations that circumvent EGFR inhibition).

While this may bring optimism to patients and investors alike, Ken Walz, my colleague at Popper and Co., has a warning:

“Don’t discount the economic impact of this new world of cancer therapies. Pharmaceutical companies will at first be hesitant to abandon their blockbuster strategy. Niche drugs would not be sustainable under their cost structure. If discovery and development costs stay the same, the price of niche drugs would have to be very, very high. But if ASCO’s goals come true, R&D costs could realistically come down. And a portfolio of niche drugs could work very well, indeed.”

Good food for thought, considering how many times that light at the end of the cancer therapy tunnel was just a reflection off more muck. What do you think? What does the future of cancer therapy look like? Or the future of pharmaceutical development and R&D investment, for that matter? Share your thoughts with us.

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Are We at the End of a Long, Murky Slog in Cancer Treatment?

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November 4th, 2011
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For many years, a lot of people (including us) have called for a new way to look at, diagnose, and treat cancer. This means changing everything – from how we classify cancer to research strategies to treatment regimens. It’s been a long slog, through murky data and lots of failures, but now we’re finally seeing targeted treatments, matched with diagnoses to select the right niche of patients. Best of all, there is strong evidence to suggest that those treatments may work very well in those patient cohorts.

These are unlike most current cancer therapies, which are marked by “broad brush” descriptions (“a breast cancer drug”) and expensive price tags that can wipe out savings, burden insurance companies, and may have little benefit. But the FDA has just approved a series of treatments (albeit for rarer and later-stage cancers) that come with companion diagnostics to make sure the patient is the right one (i.e., has the right biomarker profile) for that drug. Identification of these patients prior to treatment means that while the treatments are still very costly, they stand a much better chance of actually working.

Just recently, the FDA approved (under its fast-track NDA approval system):

Zelboraf: indicated to treat metastatic or unresectable melanoma in about half of melanoma patients whose tumors have the V600E mutation in the BRAF gene. Clinical trials showed improvement in survival compared to other chemotherapies.   The companion diagnostic test (cobas 4800 BRAF V600 Mutation Test) costs just $150. The drug cost? $56,400 for six months. The good news? The majority of patients taking Zelboraf in the pivotal clinical trial are still alive.

Adcetris: designed to treat progressive Hodgkin’s lymphoma (HL) and anaplastic large-cell lymphoma (ALCL) by targeting chemotherapy doses to cells that carry a CD30 marker and bypassing healthy cells.  In the HL group, complete or partial shrinkage of the cancer was achieved in 73 percent of the patients who on average responded to therapy for 6.7 months.  The endpoint in the ALCL group of patients was similar to the HL group and 86 percent achieved complete or partial response on average for up to 12.6 months.

Xalkori: to treat a small subset of late-stage patients with non-small cell lung cancer (NSCLC) whose cells express the abnormal anaplastic lymphoma (ALK) protein.   In two multi-center clinical trials, complete or partial shrinkage of the cancer was achieved in 50 percent of patients with a median response of 42 weeks and 61 percent with a median response rate of 48 weeks.  The drug was developed by Pfizer and costs $115,200 per year, and the Vysis ALK Break Apart FISH Probe Kit (Abbott) is the companion diagnostic at a cost of $250.

A reduction in the time to approval is a side benefit to the strategies put forth by the drug and diagnostic companies pairing drugs with companion diagnostics – and will likely stimulate more pairing of drugs and diagnostics in the near future. As an added plus, linking diagnostics with treatments will pinpoint who’s qualified for the drug – and insurance carriers may then rejoice in the cost savings from providing coverage to only those patients who could benefit.  And, though many other patients with life-threatening cancers won’t qualify, drug developers will be able to turn their attention to looking for treatments for those non-responders.

Nonetheless, enough questions remain to create more than a little residual murkiness. Do we (or could we) know enough about enough biomarkers to make this strategy effective for more cancers? What happens when tests are developed to disqualify patients? What if biomarker tests are positive, but don’t point confidently to a certain cancer? What if a patient has several cancers, or has a cancer that has metastasized? Share your thoughts with us here.

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Moving Beyond The Whack-a-Mole Style of Cancer Treatment

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September 26th, 2011
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In his latest Wall Street Journal column (“Drugs That Are as Smart as Our Diseases”), biologist/author Matt Ridley bemoans the plummeting efficiency of drug discovery in the pharmaceutical industry. He points to a disturbing paradox: while identifying and sequencing genes of pathogens and cancer cells has become much cheaper in a short period of time, the number of new drug candidates (based at least in part on our knowledge of those genes) has dropped. According to Ridley, new molecule approvals per billions of dollars of inflation-adjusted R&D amounts to no more than one percent of the number of approvals in 1950. And as we’re all aware, this decline in innovation is all the more dire because the pharmaceutical industry needs to replace so-called “blockbuster” drugs that are about to lose their patent protections if it is to continue to keep investors satisfied and fuel future innovation.

So, why hasn’t the same industry that gave us statins, Herceptin®, and vaccines come up with a new generation of treatments? The biggest problem might lie in its success. Researchers today confront an enormous—and growing—amount of genetic and biochemical information as the search continues for newer, more effective drugs.  As we generate more data, we are increasing our understanding of the complexity of biological processes underlying disease states.  While this better understanding can lead to innovation, it also has uncovered obstacles. For example, scientists have found that signaling pathways leading to cancers are replete with redundancy, shortcuts and other molecular detours that block the activity of cancer drugs. Sometimes, these pathways can help eliminate or prevent cancer; at other times they can exacerbate it.

It also has become increasingly clear that cancers are not what we originally defined them to be. There are 200 types of cancer; most are defined by the tissue in which they are predominantly found or in which they originated (in the case of metastasis). This location-based classification was useful for surgical solutions (which were once the only options available), and could provide some sense of prognosis. However, these location-based classifications do not capture the biological diversity of cancer.

Herceptin® provides a useful glimpse into cancer’s complexity (as well as into the challenges in treating cancer’s manifestations). When introduced, Herceptin proved very effective against breast cancers triggered by mutations in HER2. However, many cancers are resistant to Herceptin, and researchers are now using a “Whack-a-Mole” approach, relying on successive hammer attacks to fight multiple mutations and pathways that pop-up to bypass effects of the “targeted” drug. In fact, Tanizaki and colleagues (full text by subscription) found that HER2, HER3 and MET are factors not only in breast cancer, but lung cancer as well. It’s possible that the “Whack-a-Mole” approach can address the multiple targets that characterize the molecular mechanisms of cancer, while addressing cancers by their genomic and signaling profiles. But that approach will become more effective in those cases where we can simultaneously hit multiple drug targets. It involves taking cancer treatment to the next level.

Clearly, finding the “moles” and utilizing “multiple hammers” will require more and more information, and represents a change in drug discovery strategy from the “one disease-one target” biochemical approach.  The World Health Organization has recommended reclassifying lung cancers (subscription required for full text) by immunohistochemical criteria, for example, and continues to work on expanding definitions of cancers to gene or cell signal.

Revisiting the earlier-raised question of “Why the dearth in a new generation of treatments,” I wonder: Will this change in drug discovery strategy help us develop more effective drugs for cancer patients? Can advances in areas like systems biology find more answers that will lead to new options in the treatment of cancer and other diseases? Can we move beyond the “Whack-a-Mole” hammer to make smarter treatments? Please share your thoughts with us here.

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TRI-CON – Diagnostics, Drug Discovery & Biologics: Oh My!

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February 21st, 2011
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Sometimes, between the hotel room, the lectures, the networking, the power lunches and the data consumption at a conference, you’re on the plane home before you have time to reflect upon why you attended in the first place. I’m excited to be heading to the 18th International Molecular Medicine Tri-Conference in San Francisco this week—and I’m setting out my reasons for going this year beforehand.

I always look forward to this conference because of its balanced range of life science topics, including those with technical, scientific, business, strategy, regulatory and reimbursement slants. Within this balanced range of topics, the Tri-Con uses a channel structure to help attendees “tune in” where they can get the biggest bang for their buck. I’m excited to learn more about the following specifics within each channel:

  1. DiagnosticsRapid changes are taking place on the diagnostics stage this year. Personally, I’m interested in molecular diagnostics, personalized diagnostics, cancer markers and circulating tumor cells (CTCs). I’ll be tuning in to discussions on the adoption and integration of the next generation of sequencing, companion diagnostics and the use of/characterization of CTCs.
  2. Drug discovery & development–Here, sessions promise updates on translational science, including the use of biomarker technology to support drug development.
  3. Biologics–This is a vast topic, but I’m especially interested in discussions on the study and use of stem cells. I’ll be looking to learn more about the applications of stem cells to support drug testing and for use as therapeutics.
  4. Cancer–For this channel, I’ll be focusing on sessions related to companion diagnostics, stratification of patient populations (including predictive and prognostic markers), and recent developments in pathway-driven or targeted drugs (a.k.a., personalized medicine).
  5. Informatics–Within this area of focus, I’ll watch for updates on methods to analyze integrated data types, workflow management and more.

The integration of each of these channels (which include more than 250 presentations), the focus throughout on industry-changing and trendsetting technologies, and the quality of keynote presenters is what distinguishes Tri-Con from other industry events. It also doesn’t hurt that more than 70 scientific posters will be displayed and that the exhibit hall is packed with vendors that present their latest products and technology (often in a manner that enables you to dig in and understand the role of the product/technology in the R&D process).

In addition to all of the educational aspects of the conference, I’m also looking forward to meeting thought leaders in many of the disciplines, and to connecting with Popper and Company clients and colleagues who will be attending.

If you’ll be there, please comment below or drop me a note, and let’s plan to connect. If you’re not attending, but are interested in any of the channels above, I hope you’ll tune back into our blog for my follow up piece post conference. As for now, I’m leaving on a jet plane…

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