About UPDDI

QSP is the New Vision of Drug Discovery and Development for Precision Medicine

Given the challenges within the pharmaceutical industry and the need for innovation in the industry, it was clear to us that an academic drug discovery institute should explore new approaches to the discovery of novel therapeutics, as well as repurposing approved therapeutics. Our strategy has been to harness the main strengths in Pittsburgh that include outstanding computational and systems biology at both the University of Pittsburgh (Pitt) and Carnegie Mellon University (CMU), the University of Pittsburgh Medical Center (UPMC), the Pittsburgh Supercomputing Center (PSC), a new initiative between Pitt, CMU and UPMC named the Pittsburgh Healthcare Data Alliance (PHDA) created to dramatically change the practice of medicine through medical informatics, as well as outstanding therapeutic area researchers and clinicians with access to crucial patient samples. These strengths encouraged us to pursue the emerging field of quantitative systems pharmacology (QSP) as a central theme. You can explore our web site to get an overview (www.upddi.pitt.edu).

The University of Pittsburgh (Pitt) has the breadth and depth to support a major effort in drug discovery and development and in cooperation with the University of Pittsburgh Medical Center (UPMC) and Carnegie Mellon University (CMU), the ability to translate basic research to clinical practice. The UPDDI has created a centralized facility and core staff with a combination of academic and industrial experience, to help collaborators translate outstanding basic science into drug discovery programs. Additionally, many of the specific functions of the drug discovery and development process are distributed across the Pitt and UPMC campuses in distinct departments, centers and institutes; especially in the Schools of Medicine and Pharmacy, as well as the Colleges of Arts and Sciences and Engineering.

QSP Programs:

The UPDDI has major efforts in three broad disease areas: 1) liver diseases; 2) metastatic cancers; and 3) neurodegenerative diseases. In addition, we have a major commitment to developing the critical QSP technologies required to optimally implement the approach including human microphysiology systems (MPS), computational models of disease progression and ADME/Tox, and computational and systems pathology to inform precision therapeutic strategies and companion diagnostics.  The UPDDI has a major commitment to creating, disclosing and patenting novel discoveries and then licensing the technologies either to existing companies or spin-off start-ups. The programs involve extensive collaborations between computational and systems biologists, clinicians, therapeutic area researchers, toxicologists, chemists, pharmacologists and engineers in Pittsburgh, as well as in other academic/medical centers, federal agencies and industry. More information is listed in the Highlights link on the home page.

Projects:

Although the UPDDI is focused on the application of QSP to the discovery and development of therapeutics, we also support smaller-scale research projects based on ligand or target-centric discovery methods that are driven by individual faculty collaborators and funded by grants covering any therapeutic area. We support the use of a range of experimental systems (e.g., yeast, C. elegans, Drosophila, and zebrafish), as well as human-derived cell/engineered tissue models early in the discovery process.

Innovations:

Quantitative Systems Pharmacology (QSP): Combination of computational and experimental methods to elucidate, design, validate and apply new pharmacological concepts and strategies to the development and use of therapeutics and diagnostics. QSP provides an integrated “systems” approach assisted by high-content screening techniques to determining mechanisms of action during discovery, development and in patients. QSP will also create the knowledge required to alter complex cellular networks with single or combination therapy, as well as to alter the pathophysiology of disease in order to optimize the therapeutic benefit, while minimizing toxicity.