Biotech Strategy Blog

Commentary on Science, Innovation & New Products with a focus on Oncology, Hematology & Cancer Immunotherapy

Posts tagged ‘Personalized Medicine’

Bevacizumab (Avastin®) should be withdrawn for metastatic breast cancer. That is the unequivocal recommendation of the Oncology Drugs Advisory Committee (ODAC) yesterday.

Despite the passionate patient advocacy in favor of continued approval, withdrawal is the right decision and it is hard to see the FDA overruling ODAC, given the safety issues such as bowel perforations and relative lack of efficacy.  The patient advocacy at this week’s public hearing was fundamentally biased, those who died early and who received no treatment benefit are not alive to stand up and share their experiences.

The bottom line is that Genentech were unable to identify the sub-set of patients who might benefit from the drug.  They simply did not have the data, and the reality is that treating all potential HER2- patients in the hope of finding the few who might respond is not a rational drug development or marketing strategy, especially when those that don’t respond may do worse on the drug.

Personalized medicine requires a thorough understanding of the science and molecular biology of a disease.  Pfizer recently showed an excellent example of this with crizotinib that targets ALK mutations in non small cell lung cancer (NSCLC).

It is disappointing that a scientifically orientated company such as Genentech would continue to try and push Avastin in Breast Cancer when the data is clearly unconvincing to ODAC.   But, if we look at how Genentech approached the Lucentis v Off-label Avastin issue in AMD, with a 40x higher cost for using Lucentis, then what we see is that commercial decisions, and maximization of profit has become more important than doing what’s right for patients.

BIO 2011 Presentation Personalized Medicine Payment Sessions

This is a flawed long-term strategy in my opinion. Society cannot afford to pay for treatments that don’t work in many patients or pay for treatments that are excessively priced. We are already seeing “pay for results” being introduced in Europe, notably England and Italy where payors are reimbursing companies only for those patients that respond.

Personalized medicine is the future. This requires targeted therapies that are aimed at patients who we can predict will have a good chance of responding based on our understanding of mutations, molecular biology and biomarkers.

Avastin in metastatic breast cancer is not an example of personalized medicine and should be withdrawn from the market for this indication.

The Boston Globe today reported that Blueprint Medicines had received $40M in Series A venture funding.

The VC funding from Third Rock Ventures to the Boston/Cambridge based company is reported to be the largest early-stage funding for a New England life sciences start-up.

Many thanks to @rndubois for his tweets about this that drew it to my attention. You can read more about the financing in Blueprint’s press release.

What makes this exciting news?  First it adds to the growing reputation of Boston/Cambridge as a hot-spot for cancer research.  Blueprint Medicines will be focused on translational medicine and the development of new kinase inhibitors for the treatment of cancer.

Secondly, it confirms what is taught at business school, that investors back management expertise and their belief in the entrepreneurs ability to execute.  In the case of Blueprint Medicines the scientific co-founders are Dr Nicholas Lyndon and Dr Brian Druker, who were instrumental in the development of imatinib (Gleevec/Glivec), a tyrosine kinase inhibitor that revolutionized the treatment of chronic myeloid leukemia (CML).

Blueprint Medicines is a company to watch for the future and Biotech Strategy Blog wishes it well in the quest for personalized medicine and more effective cancer treatments.

The launch of the company in Boston/Cambridge adds to my view that Boston is emerging as the premier biotech region on the East Coast for start-ups interested in oncology and translational medicine.

Today in the plenary session of the 102nd Annual Meeting of the American Association for Cancer Research (AACR), Lynda Chin from Dana-Farber Cancer Institute in Boston provided an excellent overview of the challenges and opportunities of translating insights from cancer genomics into personalized medicine that will benefit patients.

I unequivocally recommend listening to the webcast of the plenary when it is posted on the AACR website.

As Dr Chin stated at the start of her presentation, “cancer is fundamentally a disease of the genome.”  The goal of all cancer research is to make progress with prevention, detection and cure.

In the plenary presentation she highlighted some of the successes that have come from understanding the genome e.g. the knowledge of BRAF mutation in melanoma led to the identification of a target and development of a new drug in 8 years.  In addition to the development of novel therapeutics, genomics research has helped companies reposition drugs and she highlighted crizotinib as an example (move from C-Met to ALK inhibition in NSCLC).

These successes have “motivated researchers” according to Chin.  However, it is transformative new technology such as the next generation of sequencing technology that has heralded “a new era of cancer genomics.”  Massively parallel sequencing enables comprehensive genome characterization.

Not only has innovative new sequencing technology increased the throughput, but it has dramatically decreased the costs.  As Dr Chin noted, some have questioned whether cancer genomics is worth it?  She outlined some of the recent successes, such as BAP1 in ocular melanoma (see my previous post on this) as examples of its value.

Challenges remain such as the management of the vast amount of data that genome sequencing produces.  Data management, processing and storage remain issues, as does the need to develop a reference human genome against which a patient’s tumor profile could be compared.

And even when you find a mutation, the challenge is to separate the “drivers” from the “passengers.” This according to Chin requires a “robust statistical framework”.

Cancer signaling is not linear, but is a highly interconnected and redundant network, so it remains a big task to translate genomics into personalized medicine.  According to Dr Chin using mice as models to bridge the gap between sequencing and man may be the way forward in translating cancer genomics into personalized medicine.

error: Content is protected !!