We are reinventing the fundamental science underlying the development of new medicines and their use in individual patients.
The Laboratory of Systems Pharmacology (LSP) uses a team science approach to advance the fundamental science and technology needed to develop new medicines and personalized patient care.
We study the molecular causes of disease, how drugs exert their therapeutic and adverse effects, how clinical trials are designed and interpreted, and how machine learning and AI can help identify new molecular targets in diseases like cancer, Alzheimer’s, tuberculosis, and chronic pain.
The LSP is a research and education program that is part of the Harvard Program in Therapeutic Science (HiTS). Our organization prepares students and fellows for leadership roles in academic research, industry, and government service.
Explore LSP Research
Changing fitness effects of mutations through long-term bacterial evolution
Couce and Limdi et al 2024. Science.
A CRISPRi/a screening platform to study cellular nutrient transport in diverse microenvironments
Chidley et al. 2024. Nat Cell Biol.
OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
Ahdritz et al. 2024. Nat Methods.
High-plex immunofluorescence imaging and traditional histology of the same tissue section for discovering image-based biomarkers
Lin et al. 2023. Nature Cancer.
Sequential apoptotic and multiplexed proteomic evaluation of single cancer cells
Lecky et al. 2023. Science Advances.
Development and validation of time-to-event models to predict metastatic recurrence of localized cutaneous melanoma
Wan et al. 2024. J Am Acad Dermatol.
Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer
Lin, Wang, Coy et al. 2023. Cell
Proteomic profiling across breast cancer cell lines and models
Kalocsay et al. 2024. Sci Data.
Multi-range ERK responses shape the proliferative trajectory of single cells following oncogene induction.
Chen et al. 2024. Cell Rep.
Automated assembly of molecular mechanisms at scale from text mining and curated databases
Bachman et al. 2023. Mol Syst Biol.
Causal inference in medical records and complementary systems pharmacology for metformin drug repurposing towards dementia
Charpignon et al. 2022. Nature Communications.
Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma
Gaglia et al. 2023. Cancer Cell.
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