BioSystics, Inc., a recent spin-off from the University of Pittsburgh is seeking Series A financing to accelerate the path to patient digital twins for the pharmaceutical and healthcare industries.
The BioSystics Analytics Platform™ (BioSystics-AP™) captures, analyzes, computationally models and shares data so users can develop actionable knowledge from patient-derived experimental and in vitro model data as a major step to accelerate the path to Patient Digital Twins for precision medicine.
Pittsburgh, PA (May 9, 2022)-BioSystics, Inc., has been developing the Microphysiology Systems Database, the core of the BioSystics Analytics Platform (BioSystics-AP™), with funding over the last ten years from the National Center for Advancing Translational Sciences (NCATS). BioSystics has an exclusive license from UPitt and is offering versions of the newly branded BioSystics-AP online to non-profits and on-site to for-profit customers. An early focus of the company is the workflow from early drug discovery and development through “preclinical trials” using data generated from a broad range of advanced in vitro models. In particular, BioSystics is using patient-derived human organoid microphysiology systems (MPS) and stem cell 3D layered/bioprinted MPS that recapitulate the heterogeneity of patient diseases in different organs. The human MPS organ models can be investigated separately, or as fluidically-coupled organ subsystems, to study mechanisms of disease progression and response to therapeutic treatments. Furthermore, the safety of various therapeutics can be tested in these patient-derived MPS models before being given to the patients. Data from the patient-specific MPS can be integrated with that patient’s clinical data. The goal is to create Patient Digital Twins for precision medicine that can predict what therapeutic treatments would be best for each patient and can be used to optimally recruit the best clinical trial patient cohorts for a particular drug candidate.
Mark E. Schurdak, President of BioSystics, stated “Animal models of disease and safety are often not concordant with humans. BioSystics believes that the use of data from patient-derived, in vitro physiological models and other patient-centric data will increase the success rate in getting drugs to market and selecting therapies by providing customers with patient-relevant knowledge for making decisions”.
Digital Twins have been routinely used in aeronautics and other industrial applications for many years to decrease costs and bring safe products to market more efficiently. A Patient Digital Twin is simply a computational model, or set of models, that can be used to simulate the response of a patient, for example, to predict how a particular person’s liver responds to a drug or to predict the outcome of an individual in a clinical trial.
BioSystics’ founders have leveraged their expertise and experience in quantitative systems pharmacology, drug discovery and development, toxicology, and bioinformatics to create the BioSystics-AP. BioSystics-AP’s aggregated data set includes public domain data, patient data, and data from patient-derived in vitro physiological systems and animal models. Users can augment these data with private data to use the existing BioSystics’ models or port their own computational models to the platform to predict physiological responses to a drug, drug combinations and ultimately the response of a patient in a clinical trial. “We believe the BioSystics Analytics Platform will accelerate the path to Patient Digital Twins in the pharmaceutical and health care industries”, stated Mark Schurdak.
BioSystics, Inc. (http://biosystics.com) is an analytics company whose mission is to transform the rapidly evolving field of human in vitro experimental models of disease and ADME/Tox by providing a comprehensive computational and systems biology analytics platform. The vision is to evolve the BioSystics-AP™ to accelerate the path to Patient Digital Twins. BioSystics, Inc. is presently planning a Series A financing round.