Internal pre-proposal deadline is Monday, June 1, 2026.
Merck Research Laboratories (MRL) has invited Boston University to participate in their MRL Scientific Engagement and Emerging Discovery Science (SEEDS) Program as one of a select group of seven institutions. The program will provide BU faculty investigators with funding up to $200,000 (direct and F&A) and access to MRL scientists to advance the most innovative discoveries for therapeutic targets, pathways and technologies.
Initial, non-confidential pre-proposals must be submitted to Industry Engagement for review by Monday, June 1 to allow for internal review prior to formal submission to MRL by Thursday, June 11. Pre-proposals should be in the format required by MRL using the pre-proposal template (download). Please also include a budget using the BU internal budget template for non-federal sponsors (download).
The strongest proposals with the most compelling cases to experimentally address areas relevant for the discovery and development of protein and antibody therapeutics will be considered for funding including but not limited to the following biologics domains of strategic intent that are of most interest to MRL:
- Engineered antibody frameworks/constructs – multispecifics (geometry, avidity, robustness of assembly, T-Cell engagers with co-stimulation); reusable design modules or mutations (e.g., cell/tissue/organ targeting); cellular barrier translocation or penetration (including oral bio availability/blood brain barrier/intracellular delivery); half-life extension, effector function modulation.
- Protein engineering approaches for conditionally activated biologic therapeutics or logic-gated multispecifics for function or targeting.
- Protein expression technologies; vectors, cell lines, in vitro transcription and translation; incorporation of non-natural amino acids: platforms and technologies to reach the top candidates faster and better.
- Platforms for antibody screening utilizing miniaturization, microfluidics, multiplexing readouts – High throughput measurements to select highest performing variants and rapidly eliminate hits with poor properties.
- Antibody in silico design/prediction – Artificial intelligence/Machine Learning; advanced physics or structure-based methods to predict properties for leads with drug development characteristics.
MRL will invite and work with a selection of pre-proposals to develop and submit a full proposal in July.
Please reach out to Industry Engagement for questions and materials required for proposal submission.