AI Medical Compendium Topic

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Drug Industry

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Industry 4.0 for pharmaceutical manufacturing: Preparing for the smart factories of the future.

International journal of pharmaceutics
Over the last two centuries, medicines have evolved from crude herbal and botanical preparations into more complex manufacturing of sophisticated drug products and dosage forms. Along with the evolution of medicines, the manufacturing practices for t...

[Pharma industry reinvents itself in the turmoil. Part 1. Challenges].

Revue medicale de Liege
The pharmaceutical industry faces, as many other public and private sectors, a significant deficit in trust (medication considered too expensive, not always readily available, even if it is deemed essential, lack of financial transparency). Moreover,...

Big Techs and startups in pharmaceutical R&D - A 2020 perspective on artificial intelligence.

Drug discovery today
We investigated what kind of artificial intelligence (AI) technologies are utilized in pharmaceutical research and development (R&D) and which sources of AI-related competencies can be leveraged by pharmaceutical companies. First, we found that machi...

Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.

Molecular diversity
The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted...

Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry.

Future medicinal chemistry
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) h...

Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

mAbs
Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (...

Advancing pharmacy and healthcare with virtual digital technologies.

Advanced drug delivery reviews
Digitalisation of the healthcare sector promises to revolutionise patient healthcare globally. From the different technologies, virtual tools including artificial intelligence, blockchain, virtual, and augmented reality, to name but a few, are provid...

Trial Approach for Biomedical Products: A Regulatory Perspective.

Combinatorial chemistry & high throughput screening
The modern pharmaceutical industry is transitioning from traditional methods to advanced technologies like artificial intelligence. In the current scenario, continuous efforts are being made to incorporate computational modeling and simulation in dru...

Reliable stability prediction to manage research or marketed vaccines and pharmaceutical products. "Avoid any doubt for the end-user of vaccine compliance at time of administration".

International journal of pharmaceutics
A major challenge for the pharmaceutical/vaccine industry is to anticipate and test/control product stability, regardless of the time/temperature profile of the product, from release to administration. Current empirical stability protocols performed ...