NOVA’s approach to Model Informed Drug Development

Jules Henri Poincaré (French mathematician, 1854-1912)

Science is facts; just as houses are made of stone, so is science made of facts; but a pile of stones is not a house, and a collection of facts is not necessarily science.

Foreword

This series describes NOVA’s approach to modeling and simulation for drug development and discovery. It is neither a textbook, nor a compendium of recipes for Modeling and Simulation (M&S) or Model Informed Drug Development (MIDD) since little information on methods will be provided. The goal is rather to explain an approach, which initially might appear complicated because of its complexity, but actually represents a systematic way to obtain precise, accurate and meaningful results. To achieve such a goal, ideas and concepts from several areas such as history, epistemology, reasoning, pharmacology, drug development, data management, experience and perspectives will be presented in a holistic way. Finally, this series is neither a scientific paper, nor a review. Thus the bibliography is limited to a few articles and does not represent the important literature of the various fields covered.

NOVA's approach

The foundation for NOVA's approach could be worded as "We don't know what we know". Is this maxim the opposite of that attributed to Socrates, "All I know is that I don't know anything"? On the contrary, because the amount of knowledge accumulated during the twenty four centuries that separate us from Socrates is so substantial, the major problem is not the gap between what we have learned and what remains to be learned but rather the fact that the human brain is not anymore capable of handling the amount of available knowledge, even in focused areas of science[1]

Table of content

Part 1. Introductory remarks

Part 2. NOVA’s approach reconciles knowledge with data to predict clinical outcomes

Part 3. NOVA’s Modeling and Simulation approach

Part 4. Responders - the M&S perspective

Part 5. Examples of Effect Model applications

Part 6. Are M&S outputs real?

Part 7. What can NOVA’s approach be used for?

Part 8. Expected consequences on R&D and future of MIDD

Part 9. Conclusions