BioSystics – light background

Our Vision:
To provide a “Patient Digital Twins” platform containing computational models of patients derived from clinical data and patient-derived microphysiology systems for the advancement of precision medicine.

Our Mission:
Transform the rapidly evolving field of in vitro experimental models of disease and ADME/Tox ranging from traditional cell-based assays to organoids and structured microphysiology systems by providing a comprehensive computational and systems biology analytics platform. The BioSystics Analytics Platform™ accesses, manages, analyzes, shares and computationally models complex data sets from in vitro experimental models, animal models and human clinical data creating actionable knowledge and predicting biological outcomes that will accelerate and optimize drug discovery/development, as well as cosmetic, industrial and environmental chemical testing.

The BioSystics Analytics Platform™

The BioSystics Analytics Platform (BioSystics-AP™) captures, manages, analyzes, shares, and computationally models complex data sets from in vitro experimental models, animal studies, and human clinical data, creating actionable knowledge and predicting biological outcomes that optimizes precision medicine, including preclinical trials. The BioSystics-AP™ is also valuable for cosmetic, industrial and environmental chemical testing. Links to internal and external databases provide information on drugs, assays, preclinical and clinical data for model and study design, and to develop computational models. The BioSystics-AP™ provides a streamlined workflow for selecting in vitro models, implementing studies and capturing data in a central location for efficient review, analyses and computational modeling. The BioSystics-AP™ facilitates secure data sharing within a lab and organization, with collaborators, government agencies, and the research community. There are two versions of the platform: a publicly accessible for academic institutions, and a commercial version for installation and integration within the corporate infrastructure, which is being beta-tested.

Academic BioSystics Analytics Platform

Formerly the University of Pittsburgh
Microphysiology Systems Database (MPS-Db)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

BY CLICKING “MPS-Db” BELOW OR OTHERWISE ACCESSING OR USING ANY OF THE SERVICES (INCLUDING THE PUBLIC DOMAIN TOOLS), YOU ACKNOWLEDGE THAT YOU HAVE READ, UNDERSTOOD, AND AGREED TO BE BOUND BY THE TERMS OF THE ABOVE LICENSE.

Commercial BioSystics Analytics Platform

For installation on-site and integration with company infrastructure

The BioSystics Analytics Platform™
By The Numbers

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Data Dashboard

BioSystics Public Analytical Platform

Formerly the MPS Database

BioSystics Platforms

BioSystics Services

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Actionable Knowledge That Empowers

Click each item for more info
  • Evaluation of reproducibility within a study, between studies and between sites
  • Calculation of assay statistical power
  • Optimization of sample size to achieve target assay statistical power
  • Assessment of potency and efficacy
  • Comparison of effects/liabilities within and across compound series
  • Selection of compounds for advancement
  • Design of better in vitro organ and disease models
  • Selection of reference compounds for model and study design
  • Informed assessment of toxic liabilities
  • PBPK prediction of exposure and clearance
  • Provides testable hypotheses
  • Additional computational models in development
  • Clinical trial design based on dose predictions and ‘omics correlations
  • Selection of compounds to advance to animal models
  • Estimation of threshold limits for exposure
How we're different

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Our promise

Your online success is our singular goalAnro blen kjdf lrutrum

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Aggregation of study results and clinical information

Design in vitro organ and disease models Selection of reference compounds Informed assessment of toxic liabilities Machine learning and computational modeling and providing testable hypotheses

Statistical comparisons

Enables validation of in vitro models

Site Audits

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Content Creation

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