Merck Research Laboratories Scientific Engagement and Emerging Discovery Science Program
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 eight institutions. The program will provide BU faculty investigators with funding up to $200,000 (direct plus 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 Wednesday, July 16th to allow for internal review prior to formal submission to MRL by Wednesday, July 23rd. Pre-proposals should be in the format required by MRL using this template (Kerberos login required). Please also include a budget using the BU internal budget template for non-federal sponsors.
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 – multi-specifics (geometry, avidity, robustness of assembly); 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; diversity of hits/starting points.
- 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 antibody winners 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.
- Protein engineering approaches for conditionally activated biologic therapeutics.
- Bioconjugate strategies addressing acquired resistance, treatment-related adverse effects including noncytotoxic payloads.
MRL will invite and work with a selection of pre-proposals to develop and submit a full proposal in early August.
Please reach out to Industry Engagement for questions and materials required for proposal submission