AIMC Topic: Drug Development

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Trained Immunity: RoadMap for drug discovery and development.

eLife
Trained Immunity is the nonspecific (pathogen agnostic) memory of innate immune cells, characterized by altered responses upon secondary stimulation. This review provides a RoadMap for the discovery and development of therapeutics targeting Trained I...

Catalyzing change in MID3 through globalization, education, and innovation.

Journal of pharmacokinetics and pharmacodynamics
The landscape of pharmaceutical research and drug development is undergoing a significant evolution, with Model-Informed Drug Discovery and Development (MID3) as a transformative approach to accelerate innovation. Realizing the full potential of MID3...

Current Status on the Convergence of Artificial Intelligence and Formulation Development in Industry: A Review.

AAPS PharmSciTech
Since Pfizer developed the mRNA vaccine for COVID-19 by leveraging artificial intelligence (AI) for designing the vaccine, integrating AI and allied domains in the drug development process has escalated at an unimaginable rate. Owing to the complex a...

Opportunities for AI-based Model-informed Drug Development: A Comparative Analysis of NONMEM and AI-based Models for Population Pharmacokinetic Prediction.

The AAPS journal
Model-informed drug development (MIDD) plays an important role in pharmacometrics by leveraging mathematical models to optimize drug dosing strategies. Traditional methods such as nonlinear mixed effects modeling (NONMEM) have long been the gold stan...

From Liquid SNEDDS to Solid SNEDDS: A Comprehensive Review of Their Development and Pharmaceutical Applications.

The AAPS journal
The liquid and solid formulations of self-nano-emulsifying drug delivery systems (SNEDDS) have garnered significant attention in the pharmaceutical field for their ability to enhance the solubility and absorption of hydrophobic drugs. While both liqu...

Recurrent Neural Networks Predict Future Peptide Aggregation for Drug Development.

Molecular pharmaceutics
Physical stability of an active pharmaceutical ingredient (API) is a key consideration in the development of a pharmaceutical drug. Solution conditions such as pH, excipient concentrations, and storage temperatures can impact the physical stability o...

Looking back to move forward: can historical clinical trial data and machine learning drive change in participant recruitment in anticipation of future value assessments?

Trials
Drug development is an expensive endeavor, with costs averaging $879.3 million and only 14.3% of them ultimately securing regulatory approval. One fundamental challenge is ensuring that the enrolled patient population in a clinical trial accurately r...

Molecular dynamics simulations of proteins: an in-depth review of computational strategies, structural insights, and their role in medicinal chemistry and drug development.

Biological cybernetics
Molecular dynamics (MD) simulations have emerged as a powerful and extensively employed tool in biomedical research, offering insights into intricate biomolecular processes such as structural flexibility and molecular interactions, and playing a pivo...

Unveiling anticancer peptides; from the mechanisms of action to their development through artificial intelligence.

European journal of pharmacology
Cancer is a leading cause of death worldwide and a major burden on the healthcare system. Current treatment methods are limited as they have low selectivity, unspecific targeting and increasing multidrug resistance. Therefore, newer modes of therapeu...

Ever-Increasing Role of Computational Tools in Solid-State Pharmaceutics: Advancing Drug Development with Enhanced Molecular Understanding and Risk Assessment.

Molecular pharmaceutics
The field of solid-state pharmaceutics comprises a broad range of investigations into various structural aspects of pharmaceutical solids, establishing a rational structure-property correlation. These solid systems allow the tunability of the physico...