Project Term
–
The University of North Carolina at Chapel Hill
Chapel Hill, NC
United States
Project Summary
I will advance precision combination therapy for blood cancers by computational and experimental pharmacology. In large B-cell lymphoma we will analyze and model subtype-guided pola-vedotin, genome-guided targeted therapy trials, and MRD-based care. In T-cell lymphomas, drug profiling and CRISPR screens will identify response predictors for subtype-specific regimens. In multiple myeloma we will analyze trials to resolve when intensified first-line regimens are superior to sequential therapy.
Lay Abstract
Many lymphomas can be cured when initially treated with the right combinations of medicines. Finding more effective and tolerable combinations is difficult. Nearly all approved therapies work well for some patients but do not work well for others, and new combination regimens often fail in clinical trials because they are not matched to the patients most likely to benefit. Safety is another challenge: standard lymphoma treatments already include many therapies, so adding more can cause serious side effects. My research aims to improve efficacy and tolerability by advancing our ability to personalize combination therapies for blood cancers.
My team integrates laboratory experiments, computer models of drug action in patient populations, and analysis of data from clinical trials of single or combined medicines. These approaches allow us to connect drug mechanisms to clinical trial results and to predict which new combinations are most likely to succeed in the clinic, which is increasingly useful as dozens of new lymphoma therapies become available.
A major focus of this work is initial therapy for large B-cell lymphoma, the most common blood cancer. Not all patients are cured with standard regimens, and adding more drugs has often failed because they only work in certain subgroups or the combinations are too toxic. We are addressing these challenges by asking: How could treatment timing of new combinations remain effective but minimize toxicity? How can trials match treatments to patients most likely to benefit? Should treatments be tailored to the type of B-cell that became lymphoma? Can blood tests for tumor DNA select patients who need intensified therapy, while sparing others unnecessary toxicity?
Another part of the project investigates peripheral T-cell lymphomas, which remain difficult to treat. We will use genetic screens and a diverse panel of T-cell lymphomas to understand which tumors are sensitive to which drugs, enabling future trials to select treatments based on tumor characteristics.
Finally, we will analyze clinical trials in multiple myeloma to investigate the timing of adding new therapies to combinations, and whether using them earlier or later affects overall treatment effectiveness and survival.
By matching the right medicines to the right patients at the right time, this research aims to improve cure rates, reduce unnecessary toxicity, and help deliver more effective, more personalized treatments for people with blood cancers.
Program
Grant Subprogram