The LSP is an NIH National Center for Systems Biology and an NIH LINCS Project Data and Signature Generation Center. An overview of additional government-funded LSP research projects is provided below. LSP Investigators are also involved in collaborations with industry partners that apply a combination of multiplex measurement and computational modeling to understand mechanisms of drug action.
The HMS Laboratory of Systems Pharmacology (P50 GM107618-03)
This multi-investigator grant aims to apply a systems biology approach to understanding drug action in man. The grant establishes the Harvard-based Laboratory of Systems Pharmacology as an NIH National Center of Systems Biology (NCSB) focused on understanding drug responses at a network level.
Pharmaco-Response Signatures & Disease Mechanism – NIH LINCS Center (NHGRI U54HG006097)
The Harvard Medical School Library of Integrated Network-based Cellular Signatures (LINCS) Center was established in October 2010 to create libraries of measurable cellular responses or signatures that describe how cells respond to perturbation. As of March 2017, six centers across the U.S. participate in the NIH LINCS program. The aim of the HMS LINCS Center is to create signatures that measure the responses of cells derived from different human tissues to therapeutic drugs. Much of the work focuses on tumor cells (from breast, liver and colon), but we also study primary human cells from normal and diseased patients. As perturbing agents, our focus is on small molecule kinase inhibitors, which are a leading class of therapeutic agents for treatment of cancer, autoimmune and other diseases.
Big Mechanism: Programmatic modeling for reasoning across complex mechanisms (W911NF-14-1-0397)
The DARPA Big Mechanism program aims to automatically assemble computational models of cancer signaling by reading the scientific literature. We have developed the Integrated Network and Dynamical Reasoning Assembler (INDRA), a system that can collect millions of elementary mechanisms from the literature (with the help of reading systems such as REACH and TRIPS), and assemble them into models that can explain and predict cellular response to perturbations. We have deployed The Ras Machine @, an autonomously running system which reads relevant new publications as soon as they appear (hundreds of articles each day) and integrates newly learned information into an ever-growing model of Ras biology which is immediately published. This work has been featured in a Wired UK article by DARPA’s former director Arati Prabhakar.
Communicating with Computers: Active Context (W911NF-15-1-0544)
The DARPA Communicating with Computers (CwC) program develops technologies for a new generation of human-machine interaction in which machines act as proactive collaborators rather than merely problem solving tools. We are developing an interactive dialogue system which allows scientists to interact with a computer partner – one that is able to harness knowledge extracted from the biomedical literature – to construct and test hypotheses about molecular systems. Listen to a podcast about our work, which appeared in The Guardian.