Category Archives: BigPharma

What Are You Waiting For- A Certain Shade of Green? Core Science & Tech Development

Solving difficult scientific or engineering problems has proven itself to be the greatest benefactor of long-term growth and development. However, finding support for fundamental technological developments has come increasingly under fire in recent years.

From “Amusing Ourselves to Death” By Neil Postman, a book about the possibility that Aldous Huxley, not Orwell, was right.

It is not just crying wolf, and we have all heard this message before, funding for science is low, the space program takes cuts, fewer technical majors, Justin Bieber is more popular than The Doors.

A fantastic metric to determine whether our resources, in sum, are being allocated fruitfully is to look at pooled returns of venture fund indexes. Starting with its birth in the 1960s, to the 1990s. Venture capital had excellent returns, and it often closely associated with the high-capital, slow-growth, semiconductor and biotechnology industries.

VC funds have posted negative mean and median returns, starting in 1999 through the present. A small fraction of firms are the exception.

In the new millennium however, we have encountered a new paradigm for returns amongst these indexes, a shift from funding transformational technologies to supporting companies solving incremental, or “hype” based problems. A shift from long-term garden like growth, to one equivalent to big game hunting. Steve Blank, who is invested in Ayasdi, said it best recently, stating:

If investors have a choice of investing in a blockbuster cancer drug that will pay them nothing for fifteen years or a social media application that can go big in a few years, which do you think they’re going to pick? If you’re a VC firm, you’re phasing out your life science division.

This perspective is beyond the bubble argument, or the oscillations of markets. It marks the creeping penetration of triviality into our investment culture. Furthermore, it is not a decision by any individual, rather the whole return of investment ecosystem has created an illusion highlighting consumer, social, and entertainment products.

Illumina HiSeq systems, a core technology driving contemporary life-science discoveries.

Venture is often associated with bravely expanding our horizons, to seek out new lands, and bring back riches that will ensure growth for generations to come. Where will we go after all the shoe stores, and match-makers have migrated online? Once the saturation of social media has reached nauseating ubiquity? To truly create long-term returns, that assure the future financial stability of the investor, scientist/engineer, and society we must lead, not follow the bandwagon, or be part of the “me too” culture.


“Cambridge Associates LLC U.S. Venture Capital Index® And Selected Benchmark Statistics” 2011

“Lessons from Twenty Years of the Kauffman Foundation’s Investments in Venture Capital Funds and The Triumph of Hope over Experience” 2012

“What Happened To The Future” – FoundersFund Manifesto


Filed under BigPharma, Genomics

Closing The Gap Between Computational & Pharmaceutical Innovation

When confronted with the mortality of life, it becomes painfully clear that medicine has not been able to keep up with information and computational innovations. At the heart of the problem stands  the drug development process, where an average of 5 to 10 years of research and billions of dollars worth of investment often fails to produce a product.

Drug Probability of Success to Market

Figure 1 | Probability of success to market from key milestones. Data: cohort of 14 companies.

In the past few years, molecules in development have seen a frightening rate of attrition. The most capital and resource intensive period comes during the clinical trials, which can be broken-down into the following stages: Phase I trials evaluate if a new drug is safe, Phase II and Phase III trials assess a drug’s efficacy, monitor side effects, and compare the drug to similar compounds already on market. Recent studies by the Centre for Medicines Research, places Phase II success rates at 18%, lower than at any other time during drug development [1]. Spending on average of $300 million to $1 Billion up until this point of research is par for the course [2].

Successful Discovery Strategies

Figure 2 | Computer-assisted screenings and traditional discovery strategy distributions of new molecular entities (NME). Followers are in the same class as previously approved drugs.

By contrast, computational drug design strategies have made tremendous advances in the new millennia with new tools to identify targets and virtual screening assays. These include structure-based tools to lead identification and optimization utilizing X-ray crystallography. As well as, high-throughput target-based screenings of key protein families like G protein-coupled receptors. Promising indicators of computational drug designs are encouraging new companies to court Big Pharma, who to-date have relied on academia or internal projects for computation. For a company like GeneDrop, even a fraction of the development budget would be adequate to deliver favorable results.

Drug development’s addressable market-size for global corporations such as Novartis or Roche, which have between 20-100 molecules in the pipeline at a given time, is estimated at  $1.11 Trillion in 2011; down from $1.24 Trillion in 2001 [2]. There are approximately ten large pharmaceutical companies and many small ones with one or two late-stage molecules in development.

Early-Stage Computational Drug Design

Fig 3 | Early-stage computational drug design flow

To-date, most computation in the space has been limited to early-stage research on the discovery of molecules prior to the clinical trial phases. However, the fall in market cap has sent drug companies scrambling as patents on existing blockbuster drugs near expiration, and those in development see increasingly high failure rates. This begs the question: why are computational resources being spent in the early-stage, when most failures occur in the late-stage, during Phase II?


Fig 4 | Pharmacogenomics attempts to correlate how individuals will respond to drugs based genomic variability.

As always, cost has been a primary factor. Late-stage computation has meant analysis of bio-metric data, which has been limited to blood-work and questionnaires of trial subjects. The pie in the sky of course, has always been genomics, the price of which was deemed too high. Even up to a couple of years ago, it would cost over $10,000 to sequence an individual. With Phase II and III trials consisting of hundreds to thousands of patients, the method was rarely used. As of the last few months this is no longer the case, with the cost hovering around $5,000 and quickly approaching $1000 per patient.

So, we are faced with an enticing opportunity for information technology to rescue a high-capital, old-world industry. Threading this needle however is no easy task; entrenched industries with high quarterly revenues are notoriously conservative when adopting innovation, especially from the outside. Adding to this is the high barrier of the technical languages of the hard-sciences and the networking culture of global corporations. Luckily both are boundaries which have been broken before in other industries and we can be optimistic; if anyone can break it, it is the passionate and talented.


[1] Trial watch: Phase II failures: 2008–2010 by J. Arrowsmith – Nature Reviews Drug Discovery 10, 328-329 (May 2011) | doi:10.1038/nrd3439

[2] – Fig 1- A decade of change by J. Arrowsmith – Nature Reviews Drug Discovery 11, 17-18 (January 2012) | doi:10.1038/nrd3630 

[3] – Fig 2- How were new medicines discovered? by David C. Swinney & Jason Anthony – Nature Reviews Drug Discovery 10, 507-519 (July 2011) | doi:10.1038/nrd3480

[4] – Fig 4 – Genomics in drug discovery and development by Dimitri Semizarov, Eric Blomme (2008) ISBN 0470096047, 9780470096048

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Drug Development from Binary to Gradient Model

Earlier this year a study by the Center for the Study of Drug Development at Tufts University placed the cost of developing a new drug at $1.3 billion [1].

Distribution of Development Funding

Though the number is contested by other researchers [2], it is well within the trend of pervious studies and has now been widely accepted as an industry wide average. Exacerbating the issue is the all or nothing nature of drug development, where failure during any phase of clinical trials can cause the termination of a project. It is therefore advantageous to consider technologies that will reduce the risk of this binary success/failure model and transition to a gradient definition of therapeutic efficacy.

Trending Costs of Drug Development

Much of the high costs come in during phase 2 & 3 trials, where patient care, clinical production and regulatory leg-work consumes funds at an alarming rate. With everything riding on the individual trial subjects, their well-being directly linked to success. Undesirable reactions to experimental treatments is unavoidable and the margins for serious adverse events is kept tight by regulatory agencies to protect healthcare consumers. Often however, ground-breaking treatments have to be shelved because they affect 10-15% of trial subjects detrimentally.

RD costs of new chemical entity (NCE)

This makes any ability to view trial subjects with increased resolution and discern subtle correlations with their reactions to consumer demographics key in cutting risks of total-loss. Here I hope a story about my own experience is helpful, as I know it better than what anyone else has had to dealt with. My time at Novartis began when I was brought on-board to help with the development of a drug entering a repeat Phase IIB trial, as the first time around approximately 15% of subjects showed an adverse reaction of note.

Draft FDA Guidance on DNA Sequencing & Clinical Trials

Soon however folks began to get cold-feet, do we dump further resources behind this project or cut our losses and iterate to the next project. A third option now becoming available is that perhaps there was something specific to those 15% of patients that caused the unwanted reaction. Identifying this would allow the drug to move along its pipeline with contraindications that covered the failing demographics. No longer limiting projects to pass/fail while hedging development risks.

DiMasi et al,(2003) The price of innovation: new estimates of drug development costs
Ernst & Young Global Pharmaceutical Industry Report (2011) Progressions Building Pharma 3.0
Tufts Center for the Study of Drug Development (2011) Outlook 2011 report

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Industry & Academia, part 2: Ex Mod Op

Infamous Exubera Insulin Disaster

Opening restrictions of what a guided problem is allows us to achieve greater results.  A simple rendition of this can be seen with consumers perception of what “cures” or medicine is. The lay public expects a pill to solve our problems. Which inversely effects the professionals own vision of what their goals are. Any cure that a researcher imagines is heavily influenced by what they perceive the consumer will accept, overwhelmingly a pill or vaccine.  When new forms of delivery are brought to the edge of market they are often marred internally as “untested” or the cost of implementation by an older method is brought to attention. Exubera was developed when predictions throughout the healthcare industry pointed to a diabetes epidemic, which of course we are smack in the middle of now. In that climate a non-invasive inhalable insulin seemed like it would pay its weight in gold, it didn’t.

Today, the oracles in their glass towers predict a surge in respiratory illness. Rightfully pointing to developing nations, i.e. China, India and their falling air qualities & rising numbers of healthcare consumers. Guiding research towards COPD, cystic fibrosis and others, all of which are significant causes of suffering. Chasing after the dollar often is the best method for innovation; healthcare however, has often demonstrated to be a more complex system requiring greater foresight than simply following consumers pocketbooks and wants. Adding to this are the already strict standards which government agencies apply and by so doing hinder the progress of medicine.

This often brings up the fear that the regulations were placed to keep the public safe and still to-date so many dangerous drugs make it to market every year; a moot point, in that many of the addictive, high risk drugs which make it to market are often brought about by public want. Pain-killers & anti-depressants, all poster ads for substance abuse and hollywood over-doses. Truly increasing life span and quality significantly, requires a new paradigm of for-profit research and public perception of medicine. Extinctus Modus Operandi.

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