Applications of artificial intelligence and machine learning algorithms to crystallization
Artificial intelligence and specifically machine learning applications are nowadays used in a
variety of scientific applications and cutting-edge technologies, where they have a …
variety of scientific applications and cutting-edge technologies, where they have a …
Harnessing machine learning for development of microbiome therapeutics
The last twenty years of seminal microbiome research has uncovered microbiota's intrinsic
relationship with human health. Studies elucidating the relationship between an unbalanced …
relationship with human health. Studies elucidating the relationship between an unbalanced …
Concerning elusive crystal forms: The case of paracetamol
Y Liu, B Gabriele, RJ Davey… - Journal of the American …, 2020 - ACS Publications
Increasing commercial application of state of the art crystal structure prediction to aid solid
form discovery of new molecular entities allows the experimentalist to target the polymorphs …
form discovery of new molecular entities allows the experimentalist to target the polymorphs …
Molecular, solid-state and surface structures of the conformational polymorphic forms of ritonavir in relation to their physicochemical properties
C Wang, I Rosbottom, TD Turner, S Laing… - Pharmaceutical …, 2021 - Springer
Purpose Application of multi-scale modelling workflows to characterise polymorphism in
ritonavir with regard to its stability, bioavailability and processing. Methods Molecular …
ritonavir with regard to its stability, bioavailability and processing. Methods Molecular …
Applications of machine learning in solid oral dosage form development
H Lou, B Lian, MJ Hageman - Journal of Pharmaceutical Sciences, 2021 - Elsevier
This review comprehensively summarizes the application of machine learning in solid oral
dosage form development over the past three decades. In both academia and industry …
dosage form development over the past three decades. In both academia and industry …
Recent advances in co-processed APIs and proposals for enabling commercialization of these transformative technologies
L Schenck, D Erdemir, L Saunders Gorka… - Molecular …, 2020 - ACS Publications
Optimized physical properties (eg, bulk, surface/interfacial, and mechanical properties) of
active pharmaceutical ingredients (APIs) are key to the successful integration of drug …
active pharmaceutical ingredients (APIs) are key to the successful integration of drug …
Insights into cation ordering of double perovskite oxides from machine learning and causal relations
This work investigates origins of cation ordering in double perovskites using first-principles
theory computations combined with machine learning (ML) and causal relations. We have …
theory computations combined with machine learning (ML) and causal relations. We have …
Designing workflows for materials characterization
Experimental science is enabled by the combination of synthesis, imaging, and functional
characterization organized into evolving discovery loop. Synthesis of new material is …
characterization organized into evolving discovery loop. Synthesis of new material is …
Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides
The computational design of suitable multiferroic double perovskite oxides requires finding
materials that exhibit sizable polarization, magnetization, and coupling between them …
materials that exhibit sizable polarization, magnetization, and coupling between them …
Machine learning-based solubility prediction and methodology evaluation of active pharmaceutical ingredients in industrial crystallization
Solubility has been widely regarded as a fundamental property of small molecule drugs and
drug candidates, as it has a profound impact on the crystallization process. Solubility …
drug candidates, as it has a profound impact on the crystallization process. Solubility …