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AAPS J ; 24(1): 19, 2022 01 04.
Article in English | MEDLINE | ID: covidwho-1605878


Over the past decade, artificial intelligence (AI) and machine learning (ML) have become the breakthrough technology most anticipated to have a transformative effect on pharmaceutical research and development (R&D). This is partially driven by revolutionary advances in computational technology and the parallel dissipation of previous constraints to the collection/processing of large volumes of data. Meanwhile, the cost of bringing new drugs to market and to patients has become prohibitively expensive. Recognizing these headwinds, AI/ML techniques are appealing to the pharmaceutical industry due to their automated nature, predictive capabilities, and the consequent expected increase in efficiency. ML approaches have been used in drug discovery over the past 15-20 years with increasing sophistication. The most recent aspect of drug development where positive disruption from AI/ML is starting to occur, is in clinical trial design, conduct, and analysis. The COVID-19 pandemic may further accelerate utilization of AI/ML in clinical trials due to an increased reliance on digital technology in clinical trial conduct. As we move towards a world where there is a growing integration of AI/ML into R&D, it is critical to get past the related buzz-words and noise. It is equally important to recognize that the scientific method is not obsolete when making inferences about data. Doing so will help in separating hope from hype and lead to informed decision-making on the optimal use of AI/ML in drug development. This manuscript aims to demystify key concepts, present use-cases and finally offer insights and a balanced view on the optimal use of AI/ML methods in R&D.

Artificial Intelligence , Clinical Trials as Topic , Computational Biology , Drug Development , Machine Learning , Pharmaceutical Research , Research Design , Animals , Artificial Intelligence/trends , Computational Biology/trends , Diffusion of Innovation , Drug Development/trends , Forecasting , Humans , Machine Learning/trends , Pharmaceutical Research/trends , Research Design/trends
Pharm Res ; 38(1): 3-7, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1384537


Biologics are complex pharmaceuticals that include formulated proteins, plasma products, vaccines, cell and gene therapy products, and biological tissues. These products are fragile and typically require cold chain for their delivery and storage. Delivering biologics, while maintaining the cold chain, whether standard (2°C to 8°C) or deepfreeze (as cold as -70°C), requires extensive infrastructure that is expensive to build and maintain. This poses a huge challenge to equitable healthcare delivery, especially during a global pandemic. Even when the infrastructure is in place, breaches of the cold chain are common. Such breaches may damage the product, making therapeutics and vaccines ineffective or even harmful. Rather than strengthening the cold chain through building more infrastructure and imposing more stringent guidelines, we suggest that money and effort are best spent on making the cold chain unnecessary for biologics delivery and storage. To meet this grand challenge in pharmaceutical research, we highlight areas where innovations are needed in the design, formulation and biomanufacturing of biologics, including point-of-care manufacturing and inspection. These technological innovations would rely on fundamental advances in our understanding of biomolecules and cells.

Biological Products/standards , COVID-19/therapy , Pharmaceutical Research/standards , Refrigeration/standards , Biological Products/therapeutic use , COVID-19/epidemiology , Humans , Pharmaceutical Research/trends , Refrigeration/trends , Vaccines/standards , Vaccines/therapeutic use