A modeling informed quantitative approach to salvage clinical trials interrupted due to COVID‐19

Geerts, Hugo; van der Graaf, Piet

Many ongoing Alzheimer's disease central nervous system clinical trials are being disrupted and halted due to the COVID‐19 pandemic. They are often of a long duration’ are very complex; and involve many stakeholders, not only the scientists and regulators but also the patients and their family members. It is mandatory for us as a community to explore all possibilities to avoid losing all the knowledge we have gained from these ongoing trials. Some of these trials will need to completely restart, but a substantial number can restart after a hiatus with the proper protocol amendments. To salvage the information gathered so far, we need out‐of‐the‐box thinking for addressing these missingness problems and to combine information from the completers with those subjects undergoing complex protocols deviations and amendments after restart in a rational, scientific way. Physiology‐based pharmacokinetic (PBPK) modeling has been a cornerstone of model‐informed drug development with regard to drug exposure at the site of action, taking into account individual patient characteristics. Quantitative systems pharmacology (QSP), based on biology‐informed and mechanistic modeling of the interaction between a drug and neuronal circuits, is an emerging technology to simulate the pharmacodynamic effects of a drug in combination with patient‐specific comedications, genotypes, and disease states on functional clinical scales. We propose to combine these two approaches into the concept of computer modeling‐based virtual twin patients as a possible solution to harmonize the readouts from these complex clinical datasets in a biologically and therapeutically relevant way.