Lost in translation: the valley of death across preclinical and clinical divide–identification of problems and overcoming obstacles
AA Seyhan - Translational Medicine Communications, 2019 - Springer
A rift that has opened up between basic research (bench) and clinical research and patients
(bed) who need their new treatments, diagnostics and prevention, and this rift is widening …
(bed) who need their new treatments, diagnostics and prevention, and this rift is widening …
Machine learning in cardiovascular medicine: are we there yet?
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from
data, allowing computers to find hidden insights without being explicitly programmed where …
data, allowing computers to find hidden insights without being explicitly programmed where …
The 'Digital Twin'to enable the vision of precision cardiology
J Corral-Acero, F Margara, M Marciniak… - European heart …, 2020 - academic.oup.com
Providing therapies tailored to each patient is the vision of precision medicine, enabled by
the increasing ability to capture extensive data about individual patients. In this position …
the increasing ability to capture extensive data about individual patients. In this position …
Drug repurposing for antimicrobial discovery
Antimicrobial resistance continues to be a public threat on a global scale. The ongoing need
to develop new antimicrobial drugs that are effective against multi-drug-resistant pathogens …
to develop new antimicrobial drugs that are effective against multi-drug-resistant pathogens …
Systematic integration of biomedical knowledge prioritizes drugs for repurposing
The ability to computationally predict whether a compound treats a disease would improve
the economy and success rate of drug approval. This study describes Project Rephetio to …
the economy and success rate of drug approval. This study describes Project Rephetio to …
Machine learning in drug design: Use of artificial intelligence to explore the chemical structure–biological activity relationship
The paper presents a comprehensive overview of the use of artificial intelligence (AI)
systems in drug design. Neural networks, which are one of the systems employed in AI, are …
systems in drug design. Neural networks, which are one of the systems employed in AI, are …
Artificial intelligence, machine learning, and drug repurposing in cancer
Z Tanoli, M Vähä-Koskela… - Expert opinion on drug …, 2021 - Taylor & Francis
Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs
for new medical indications. Several machine learning (ML) and artificial intelligence (AI) …
for new medical indications. Several machine learning (ML) and artificial intelligence (AI) …
On the Integration of In Silico Drug Design Methods for Drug Repurposing
E March-Vila, L Pinzi, N Sturm, A Tinivella… - Frontiers in …, 2017 - frontiersin.org
Drug repurposing has become an important branch of drug discovery. Several
computational approaches that help to uncover new repurposing opportunities and aid the …
computational approaches that help to uncover new repurposing opportunities and aid the …
Artificial intelligence in drug discovery: a comprehensive review of data-driven and machine learning approaches
As expenditure on drug development increases exponentially, the overall drug discovery
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …
Looking beyond the hype: applied AI and machine learning in translational medicine
Big data problems are becoming more prevalent for laboratory scientists who look to make
clinical impact. A large part of this is due to increased computing power, in parallel with new …
clinical impact. A large part of this is due to increased computing power, in parallel with new …