Technologies

Pharmaceutical Sciences

Title:

Modeling of Drug - loading biopolymers with high specificity and selectivity by artificial intelligence approaches

Area:

Pharmaceutical Sciences

Focus Area:

Digital Health, Biomaterials designing

Status:

proof of concept

Social Benefits:

Computational descriptors of drug, functional monomer and mobile phase calculated imprinting factors lead to efficient MIPs that are specific to a drug. As the drug loaded MIPs neural network ANN studies are unexplored , our proposal will be challenging and have a lot of impact on understanding drug delivery mechanisms in a broad spectrum of cancers.

Developing Agency:

Amrita School Of Biotechnology, Kerala

Technology Readiness Index:

TRL 2

Source Title:

Data sourced from Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology (DBT)

Brief Description

Description :

ANN based drug loading molecular imprinting polymers MIPs design will be exciting to develop highly specific and selectively recognising the targeted site. In developing in silico MIPs which helps to understand the impact of binding and drug release efficiency further reducing the time, cost.

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