Automation and data-driven design of polymer therapeutics.

Automation and data-driven design of polymer therapeutics. Adv Drug Deliv Rev. 2020 Nov 23;: Authors: Upadhya R, Kosuri S, Tamasi M, Meyer TA, Atta S, Webb MA, Gormley AJ Abstract Polymers are uniquely suited for drug delivery and biomaterials applications due to tunable structural parameters such as length, composition, architecture, and valency. To facilitate designs, researchers may explore combinatorial libraries in a high throughput fashion to correlate structure to function. However, traditional polymerization reactions including controlled living radical polymerization (CLRP) and ring-opening polymerization (ROP) require inert reaction conditions and extensive expertise to implement. With the advent of air-tolerance and automation, several polymerization techniques are now compatible with well plates and can be carried out at the benchtop, making high throughput synthesis and high throughput screening (HTS) possible. To avoid HTS pitfalls often described as "fishing expeditions," it is crucial to employ intelligent and big data approaches to maximize experimental efficiency. This is where the disruptive technologies of machine learning (ML) and artificial intelligence (AI) will likely play a role. In fact, ML and AI are already impacting small molecule drug discovery and showing signs of emerging in drug delivery. In this review, we present state-of-the-art research in drug delivery, gene delivery, antimicrobial polymers, and ...
Source: Advanced Drug Delivery Reviews - Category: Drugs & Pharmacology Authors: Tags: Adv Drug Deliv Rev Source Type: research