A recent chat with Palisade customer
Vertex Pharmaceuticals reinforced something I learned a few years ago when I was working with a biotechnology start-up: the development of a new drug begins with a bright idea and then enters a long, dark tunnel of uncertainty and risk. The odds that the idea will ever emerge in the marketplace are very long, 10 to 1, and the costs of development are gi-normous--from $60 to $100 million to get a new drug even as far as phase 2 clinical trials. But then. . . .the payout can also be gi-normous.
At every step in the development process, pharmaceutical risk assessment is crucial to a development company's viability. The company has a pool of drug "candidates" in its so-called "pipeline," the pathway that leads a candidate from preclinical development through phases 1,2, and 3 of clinical trials and, with much luck and funding, into the market. At each stage, the pharmaceutical risk management process must weigh the probabilities and potential benefits of a drug reaching the market, factor into that calculation the optimal timing of investment in development, and decide whether and when to invest in further development.
It's a big, broad playing field for risk, and the game goes on for a long time. By necessity, the people who create the risk analysis models for pharmaceutical development have brought specialized sophistication to such analytical techniques as Monte Carlo simulation, sensitivity analysis, and decision trees. There are lessons from the pharmaceutical industry for you if, in your game, you want to play at all, you're in it for the long haul.
The increasing number of mentions of Monte Carlo simulation in the popular press usually refer to its use in the realm of finance--for such applications as determining value-at-risk, reserve estimation, and credit risk management--because this is where quantitative analysis hits us directly in the pocketbook and where the technique is relatively easy to explain. But there is a parallel upturn of coverage in the realm of medicine, particularly in pharmaceutical risk management, that is mostly taking place out of the public eye.
This coverage appears in specialized periodicals--such as
Genetic Engineering -- their online counterparts, and in the offerings of
online aggregators targeting in audiences in medicine, public health, and the pharmaceutical industry. These articles deal with statistical analyses that are not so easy to explain-- pharmaceutical risk assessment in drug trials, diagnostic probabilities in new treatment regimes, risk analysis of public health hazards--and only a limited number of readers can understand them.
I mention this parallel stream of publishing because of the sheer number of medical, pharmaceutical and biotechnology studies that rely on Monte Carlo simulation. The steady rise in the number of Google alerts I receive is pretty clear evidence that the technique has escaped corporate headquarters and is deeply entrenched in the biosciences, going to work on life-and-death issues.
Risk analysis and decision-making tools are relevant to most organisations, in most industries around the world. This is demonstrated by the speaker line-up at this year's European User Conference, an event at which we believe it is important to bring together customers from a wide range of market sectors.
We are holding '
New Approaches to Risk and Decision Analysis' at the Institute of Directors in central London on 14th and 15th April 2010. As with previous years, the programme aims to provide everyone attending with practical advice to enhance the decision-making capabilities of their organisation. Customer presentations, which offer insight into a wide variety of business applications of risk and decision analysis, include:
- CapGemini: Faldo's folly or Monty's Carlo – The Ryder Cup and Monte Carlo simulation
- DTU Transport: New approaches to transport project assessment; reference scenario forecasting and quantitative risk analysis
- Georg-August University Research: Benefits from weather derivatives in agriculture: a portfolio optimisation using RISKOptimizer
- Graz University of Technology: Calculation of construction costs for building projects – application of the Monte Carlo method
- Halcrow: Risk-based water distribution rehabilitation planning – impact modelling and estimation
- Pricewaterhouse Coopers: PricewaterhouseCoopers and Palisade: an overview
- Noven: Use of Monte Carlo simulations for risk management in pharmaceuticals
- SLR Consulting: Risk sharing in waste management projects - @RISK and sensitivity analysis
- Statoil: Put more science into cost risk analysis
- Unilever: Succeeding in DecisionTools Suite 5 rollout – Unilever's story
We will also look at the recently-launched language versions of @RISK and DecisionTools Suite, which are now available in French, German, Spanish, Portuguese and Japanese. Software training sessions will provide delegates with practical knowledge to ensure they can optimise their use of the tools and implement business best practise and methodologies.
With over 100 delegates from around the world attending, the event is also a good opportunity to network and knowledge-share with risk professionals from around the world.
»
Complete programme schedule, more information on each presentation,
and registration details
One of the most expensive passages in the long road that a new drug must take to reach the marketplace is the series of mandatory clinical trials. This past summer a "life-sciences advisory company," Value of Insight Consulting, based in Fort Lauderdale, Florida, provided a close look at the factors that make clinical trials so expensive--and so risky.
"Optimizing Global Clinical Trials," by Todd Clark, reports on the details of a complex model built with Monte Carlo software that was intended to help a pharmaceutical developer working out product strategy for clinical trials. The company's goal was to choose a country from which to launch trials for a specific drug for a specific kind of cancer. Because the primary factor in locating clinical trials is probable patient enrollment, the report provides country-by-country risk assessments for 54 factors ranging from epidemiological data to satisfaction with existing cancer therapies.
For myself, having no idea how clinic trials are organized, Clark's report is eye-opening. It gives a very clear picture of the constraints under which pharmaceutical development takes place and of the huge budgets behind the process--which helps to justify the high costs of drugs. Risk analysis should have a very happy home in this industry because the value-at-risk is very high and the probabilities are pretty sorry. As Clark reports, “On average, drug sponsors can spend over 13 years studying the benefits and risks of a new compound, and several hundred millions of dollars completing these studies before seeking FDA’s approval. About 1 out of every 10,000 chemical compounds initially tested for their potential as
new medicines is found safe and effective. . . ."
Amazingly enough in light of all this, Clark reports that the number of clinical trials is growing. It doesn't take any statistical analysis to derive from this last fact that when a drug makes it to market and makes it big there, the return on investment is a whopper.
In my last blog I mentioned there has been a dramatic upswing in the use of risk analysis and Monte Carlo software in clinical trials for new drugs. A new unpublished paper by Todd Clark of
VOI Consulting makes clear some of the reasons more people in the pharmaceutical industry are turning to operational risk software to guide them in setting up trials.
First of all, a clinical trial is probably not one trial but a process involving a series of trials, each of which takes a number of years and millions of dollars to complete. This process takes place before the company even presents the drug to the FDA for approval. Then, as the
U.S. Government Accountability Office, points out, the FDA eventually approves only 1 in 10,000 compounds a safe and effective. No wonder--again according to the GAO--"the number of new drugs being produced has generally declined while research and development expenses have been steadily increasing."
Although there are enormous profits to be made if a drug developed for a large number of patients is approved, there are great sums of money to be lost and many tricky decisions to be evaluated along the way to successful product strategies. As Clark points out, even the planning of a single clinical trial is itself fraught with uncertainty: How many subjects? What kind of subjects? What kinds of physicians? Where to hold the trials? And the answer to each of these questions is in turn a balancing out of numerous variables.
So there's plenty of risk to go around. But potentially plenty of reward. Just made for risk assessment with Monte Carlo.
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