A streamlined QSP workflow for digital-twin enabled in silico trials with chronic Hepatitis B infection

Functional cure for chronic hepatitis B infection (CHB) remains a holy grail, and multiple therapies including but not limited to siRNA, antisense oligonucleotides, immune checkpoint inhibitors, innate immunity activating molecules, therapeutic vaccination, are being evaluated either as monotherapies or combinations in clinical trials. One size does not fit all, and therefore, precision medicine strategies that identify the right patient populations for the right therapies is important. Mechanistic modelling of CHB is thus expected to play an increasing role in optimization of therapies since there are too many dosing and sequence related variables to pursue via combinatorial clinical trials. From this point of view, our group has developed a minimal QSP of CHB, and we would like to highlight how we streamline our workflows for pursuing digital-twin enabled in silico trials for ranking and optimization of combination therapies, both for enabling internal decisions as well as potential regulatory submissions.