Construction of a digital twin of chronic graft vs. host disease patients with standard of care.

There is an unmet medical need for new clinical trials to evaluate novel therapies in chronic graft-versus-host disease (cGvHD). Disease rarity, ethical issues regarding placebo arms, time, and cost impede clinical trial conduct. Digital twin (DT) technology enables virtual clinical trial arm construction using historical data, circumventing these obstacles. We evaluated the feasibility of constructing a DT trial arm using a large database of real-world clinical trial data and performed an efficacy assessment of a standard-of-care (SOC) drug to examine agreement with literature data. We constructed a flGvHD DT cohort (cGvHD patients at first-line treatment) (2042 patients; 32 cohorts) using the Trial Accelerator™ Digital Twin platform and derived an SOC arm from this cohort (flGvHD DT SOC cohort) (438 patients; eight cohorts); we analyzed the efficacy of SOC (prednisone) (overall response rate (ORR)) at six months. Our analysis results are in agreement with literature: flGvHD DT: disease onset time: 7.58 months post-allogeneic hematopoietic cell transplantation; most used graft source: peripheral blood stem cells; flGvHD DT SOC: ORR at six months for prednisone: 52.7%. It is feasible to construct a DT cohort using existing clinical trial data; a DT SOC arm can potentially replace a control arm in clinical trials.

From pharmacovigilance to pharmacoperformance.

The pharmaceutical industry is going through a period of enormous upheaval, as new sciences, technologies and commercial pressures reshape the way in which it performs research and development. PwC Consulting estimates that the top 20 companies will each need to launch between four and six times the number of drugs they currently produce, as well as improving the quality of those drugs, merely to maintain shareholder returns. This has huge implications for pharmacovigilance departments. More drugs means more trials, more patients and -- of course -- more safety reports for evaluation. The pharmacovigilance teams in most big companies are ill prepared for this transition being already stretched to the limit. But as demand for patients to participate in clinical trials increases -- with shorter development times, higher success rates in discovery and greater productivity -- so companies with a poor reputation for safety will suffer. What is it then that companies should be doing to remain compliant and be seen to be safe in the eyes of the consumer? Can pharmacoepidemiology support both molecules in the marketplace as well as those in research and development and what is really needed to enable this? Key to success will be the ability to capture, analyse and evaluate data (from disparate sources) in real time and to make rapid decisions on the appropriate course of action. Putting better structures, processes and technological platforms in place to cope with a big increase in throughput is only a short-term solution yet is it enough to fulfil the objective in the long-term of ensuring compliance and patient safety?