Accelerating Polymer discover

Accelerating Polymer Discovery via Process Intensification

In order to employ data-driven approaches to map relationships between polymer properties and biological responses, we must establish high-throughput experimental (HTE) workflows for biomaterial discovery that opens up unexplored and under-explored chemical domains to investigation. Combining chemical diversity, high discovery rates and the capacity to test multiple mechanistic hypotheses concurrently, HTE approaches will generate large experimental datasets from which structure-activity relationships can be derived via statistical learning. We will exploit synthetic workflows based on continuous flow polymerization and facilitate parallel processing from end to end, right from RDRP, to polymer purification, and finally sample preparation for physicochemical analysis and biological testing.

We are also interested in investigating physical pathways for polyelectrolyte complexation (or polyplex formation) by integrating polymer chemistry and process intensification methodologies such as turbulent micromixing to improve polyplex physical properties. By applying process intensification approaches, we seek to decouple physical properties from polymer composition. Some polymer candidates that possess optimal chemical and structural attributes would have been discarded owing to polyplex aggregation. Such polymers may have been excluded from further development without ascertaining whether aggregation resulted from deficiencies in polymer properties or arose instead from the limitations of manual mixing. My lab will redeem some of these interesting polymer candidates by reformulating and re-evaluating aggregation-prone “borderline” polymer candidates via polyplex assembly approaches based on process intensification, thereby bypassing the limitations of manual methods of polyplex assembly.

Related Publications

Combinatorial Polycation Synthesis and Causal Machine Learning Reveal Divergent Polymer Design Rules for Effective pDNA and Ribonucleoprotein Delivery
Kumar, R., Le, N., Oviedo, F., Brown, M.E., & Reineke, T.M. (2022) Combinatorial Polycation Synthesis and Causal Machine Learning Reveal Divergent Polymer Design Rules for Effective pDNA and Ribonucleoprotein Delivery. JACS Au, 10.1021/jacsau.1c00467 [PDF]   [Link to Article]
Facile synthesis of GalNAc monomers and block polycations for hepatocyte gene delivery
Bockman, M.R., Dalal, R.J., Kumar, R., & Reineke, T.M. (2021) Facile synthesis of GalNAc monomers and block polycations for hepatocyte gene delivery. Polymer Chemistry, 10.1039/D1PY00250C. [PDF]   [Link to Article]
Cationic Bottlebrush Polymers Outperform Linear Polycation Analogues for pDNA Delivery and Gene Expression
Dalal, R.J., Kumar, R, Ohnsorg, M., Brown, M.E., & Reineke, T.M. (2021) Cationic Bottlebrush Polymers Outperform Linear Polycation Analogues for pDNA Delivery and Gene Expression. ACS Macro Letters, 10, XXX, 886–893. [PDF]   [Link to Article]
Polymeric Delivery of Therapeutic Nucleic Acids
Kumar, R*., Chalarca, C.F.S.*, Bockman, M.R.*, Van Bruggen, C., Grimme. C.J., Dalal, R.J., Hanson, M.G., Hexum, J.K., & Reineke, T.M. (2021) Polymeric Delivery of Therapeutic Nucleic Acids. Chemical Reviews, 10.1021/acs.chemrev.0c00997. *equal contribution [PDF]   [Link to Article]
Efficient Polymer-Mediated Delivery of Gene- Editing Ribonucleoprotein Payloads through Combinatorial Design, Parallelized Experimentation, and Machine Learning
Kumar, R., Le, N., Tan, Z., Brown, M.E., Jian, S., & Reineke, T.M. (2020) Efficient polymer-mediated delivery of ribonucleoprotein payloads through combinatorial design & parallelized experimentation. ACS Nano, 10.1021/acsnano.0c08549. [PDF]   [Link to Article]
Block Polymer Micelles Enable CRISPR/Cas9 Ribonucleoprotein Delivery: Physicochemical Properties Affect Packaging Mechanisms and Gene Editing Efficiency.
Tan, Z., Jiang, Y., Ganewatta, M.S., Kumar, R., Keith, A., Twaroski, K., Pengo, T., Tolar, J., Lodge, T.P., Reineke, T.M. Block Polymer Micelles Enable CRISPR/Cas9 Ribonucleoprotein Delivery: Physicochemical Properties Affect Packaging Mechanisms and Gene Editing Efficiency. Macromolecules, 52, 21, 8197-8206 (2019). [PDF]   [Link to Article]