AIMC Topic: Drug Industry
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Implementation of an artificial neural network as a PAT tool for the prediction of temperature distribution within a pharmaceutical fluidized bed granulator.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Mar 15, 2016
In this study, a novel in-line measurement technique of the air temperature distribution during a granulation process using a conical fluidized bed was designed and built for the purpose of measuring the temperature under the Process Analytical Techn...
Predicting Drug-Target Interactions via Within-Score and Between-Score.
BioMed research international
Oct 12, 2015
Network inference and local classification models have been shown to be useful in predicting newly potential drug-target interactions (DTIs) for assisting in drug discovery or drug repositioning. The idea is to represent drugs, targets, and their int...
Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.
Drug development and industrial pharmacy
Aug 12, 2015
As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necess...
Computational intelligence techniques in medicine.
Computational and mathematical methods in medicine
Mar 5, 2015
A new modeling approach for quantifying expert opinion in the drug discovery process.
Statistics in medicine
Feb 23, 2015
Expert opinion plays an important role when choosing clusters of chemical compounds for further investigation. Often, the process by which the clusters are assigned to the experts for evaluation, the so-called selection process, and the qualitative r...
Computational Hit Finding: An Industry Perspective.
Journal of medicinal chemistry
Jun 12, 2025
Computational hit finding, particularly virtual screening, has been a mainstay of drug discovery campaigns for decades, providing a cost-efficient complement to wet experiments. Innovation in this space slowed considerably as these approaches converg...
NMR Pure Shift Spectroscopy and Its Potential Applications in the Pharmaceutical Industry.
Chembiochem : a European journal of chemical biology
Jun 3, 2025
H nuclear magnetic resonance (NMR) spectroscopy plays an important role in the pharmaceutical industry, but for complex substances, spectral analysis is challenging due to the narrow chemical shift range and signal splitting caused by scalar coupling...
The Role of Artificial Intelligence in Drug Discovery and Pharmaceutical Development: A Paradigm Shift in the History of Pharmaceutical Industries.
AAPS PharmSciTech
May 14, 2025
In today's world, with an increasing patient population, the need for medications is increasing rapidly. However, the current practice of drug development is time-consuming and requires a lot of investment by the pharmaceutical industries. Currently,...
Role of Artificial Intelligence in Drug Discovery to Revolutionize the Pharmaceutical Industry: Resources, Methods and Applications.
Recent patents on biotechnology
Jan 1, 2025
Traditional drug discovery methods such as wet-lab testing, validations, and synthetic techniques are time-consuming and expensive. Artificial Intelligence (AI) approaches have progressed to the point where they can have a significant impact on the d...
Integrating Model-Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation.
Clinical and translational science
Jan 1, 2025
The pharmaceutical industry constantly strives to improve drug development processes to reduce costs, increase efficiencies, and enhance therapeutic outcomes for patients. Model-Informed Drug Development (MIDD) uses mathematical models to simulate in...
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