Planning decisions on experimental design or other investments in information
Tessella can help you save costs and time in R&D through design approaches that take account of what is known, in order to fill the critical knowledge gaps efficiently. There are two key elements to this:
- Bayesian statistical approaches combine pre-existing information with potential and actual new information, to make optimal estimates
- Decision-theoretic approaches to optimal planning balance the costs of finding out against the benefits of the improved decisions that then result.
- Simulation of the experiment over plausible values of the unknown variables aids in estimating the impact of likely experimental results on subsequent real-world decisions.
How can I best decide whether a prospective drug is both safe and effective?
Tessella have been at the forefront of bayesian adaptive technologies since 1999, when we helped Pfizer to conduct the ASTIN trial, the world’s first bayesian adaptive clinical trial. Since then we have worked with the majority of the top 10 pharmaceutical companies to help them to use these technologies to reduce the time and resources required to make well-informed decisions on whether the drugs on trial, at one or more alternative doses, meet preset criteria for efficacy and safety.
How should I assess and manage the risks associated with gas exploration and transportation?
Natural gas is an inherently risky substance. It is volatile, flammable and potentially explosive. It is also a vital part of our energy economy. Tessella have worked with companies such as Shell and AGIP to understand, quantify and ultimately manage the risks to infrastructure and personnel associated with gas production.
