Artificial Intelligence for Drug Product Lifecycle Applications explains the use of artificial intelligence (AI) in drug discovery and development paths, including the clinical and postapproval phases. This book gives methods for each of the drug development steps, from the fundamentals to postapproval drug product. AI is a synergistic assembly of enhanced optimization strategies with particular applications in pharmaceutical development and advanced tools for promoting cost-effectiveness throughout the drug lifecycle. Specifically, AI brings together the potential to improve drug approval rates, reduce development costs, get medications to patients faster, and help patients comply with their treatments.
Accelerated pharmaceutical development and drug product approval rates will enable larger profits from patent-protected market exclusivity. This book offers the tools and knowledge to create the right AI strategy to extend the landscape of AI applications across the drug lifecycle. It is especially useful for pharmaceutical scientists, health care professionals, and regulatory scientists, as well as advanced students and postgraduates actively involved in pharmaceutical product and process development involving the use of artificial intelligence in drug delivery applications.
- Classifies AI methodologies and application examples into different categories representing the various steps of the drug development cycle
- Combines timely literature review with clear artworks to improve understanding
- Examines deep learning and machine learning in drug discovery
Alberto Pais is Full Professor at the University of Coimbra and Head of the Soft Matter research group of the Coimbra Chemistry Centre. Possesses considerable experience in a variety of relevant topics in the area of Computational Chemistry, Physical-Chemistry and Pharmaceutics. For each of these areas, presents high-impact publications in high-level journals, combined with various experiences in the pedagogical field.
In his scientific career, he developed work ranging from potential energy surfaces and molecular dynamics of tri- and tetraatomic systems in the gas phase to research in chemical kinetics (intersecting state model - atom transfer reactions), molecular simulation (polyelectrolytes and colloidal systems) and chemometrics (modeling, cluster analysis, factor analysis and experimental design), having also dedicated to physicochemical aspects in pharmaceutical formulation and processes (controlled release, skin and transdermal devices, including lipid nanoparticles, and development of products for oral, pulmonary administration, etc.). Other contributions cut across various scientific areas. In this context, reference should be made to the data in Scientometrics/Bibliometrics and Evaluation. It also presents smaller contributions in other areas, such as bioinformatics, cryopreservation and others.
In terms of teaching he has been involved in different disciplines. Mention, only in the computational part, the subjects taught in Numerical Methods and Programming, Chemoinformatics, Molecular Modeling, Chemometrics, Process Optimization and Scale Transposition, Chemical Equilibrium and Energetics, Pattern Recognition, and part of Fundamentals of Medicinal Chemistry among several others. He also taught, for several years, Analytical Chemistry for the Integrated Master's Degree in Pharmaceutical Sciences and Data Analysis in Analytical Chemistry for the Master's Degree in Chemistry (Quality Control Branch).
Carla Vitorino is Assistant Professor at the Faculty of Pharmacy, University of Coimbra. in the Pharmaceutical Technology area and is an integrated researcher at the Coimbra Chemistry Centre, currently a part of the associate laboratory Institute of Molecular Sciences (IMS). Her research and development activities have been fundamentally directed towards three interrelated focal points:
(i) Scientific: The primary emphasis here pertains to the formulation of more effective strategies in conjunction with drug nanodelivery systems, tailored to address multipurpose requisites within unmet medical needs. Specifically, she has been working on the application of nanotechnology in drug permeation enhancement strategies for transdermal, oral, and drug delivery systems to brain targeting. Under the projects she has coordinated and co-coordinated, she has contributed to the development of advanced nanotechnological formulations, specifically tailored for brain targeting in the context of tumor treatment and diagnosis. Through the integration of in silico-in vitro-in vivo approaches, she has fostered the development of new treatment strategies for brain tumor patients and improved diagnosis, establishing the bridge between pharmaceutical research and clinical practice. Alternative routes to access brain (e.g. intranasal administration) for delivering drugs in a more efficient way have also been explored.
(ii) Industrial: This has been grounded on the systematic deployment of frameworks driven by a quality by design (QbD) philosophy, along with process analytical technology (PAT) tools. The central tenet lies in the application of structured approaches to the development of specific drug products, including but not limited to semi-solids and injectables. Concomitantly, in-line process control and monitoring mechanisms are incorporated.
(iii) Regulatory: This has been directed to the development of analytical protocols, elaborated as surrogate modalities for clinical trials. These protocols, addressing in vitro methodologies, are designed to facilitate the bioequivalence assessment of generic topical drug products, thus holding relevance in regulatory contexts.
Sandra Nunes is Researcher at the Coimbra Chemistry Center, Department of Chemistry, University of Coimbra. Her expertise includes the development of coarse-grained models of polyelectrolyte systems, but his research interests also include the use of ab initio methods in conformational research in gas and condensed phases, Molecular Dynamics simulations applied to complex systems of chemical and biomedical interest. The aspects explored include the melting of nucleic acids and the preparation of three-dimensional structures with nucleic acids (DNA origami) with applications in gene therapy, the study of the phenomena of compaction and confinement of polyelectrolytes including crowding situations, the study of host-guest interactions, the modeling and rationalization of reaction mechanisms based on electronic structure calculations. These approaches are particularly useful for interpreting experimental results in the field of catalysis and organic synthesis, as well as for clarifying aspects related to drug/biomolecule interactions and biological membranes, both to improve the bioavailability and efficacy of drugs and to improve vectorization and transfection in biological membranes in normal and pathological situations.
Current interests focus on (i) the development of new strategies to combat bacterial resistance, through the computational design of nanotransporters based on nucleic acids, (ii) the characterization of antibacterial molecules through electronic structure calculations and computational learning methods, and (iii) the interaction of polyelectrolytes with surfaces, ranging from the interaction between therapeutic agents and biological membranes in different situations, to the adsorption of polymers and biomolecules on nanoparticle surfaces with a view to the design/preparation of different therapeutic systems.
Tânia Firmino Guerra Guerreiro da Cova is Researcher from the Coimbra Chemistry Center, Department of Chemistry, University of Coimbra. She has experience in the field of theoretical and computational chemistry in a variety of topics including the development of economically viable solutions to improve the molecular recognition of pollutants and drugs, and tumor targeting, combining supramolecular chemistry, molecular modeling and simulation and data science. She has developed molecular modeling and simulation approaches, including free energy calculations, to understand the structural, conformational and thermodynamic factors governing the formation and stability of supramolecular nanostructures based on inclusion complexes (host-guest), for drug delivery and environmental remediation. These complexes are formed between carbohydrate derivatives and biopolymers and target molecules, e.g. antibiotics, mycotoxins, pesticides.
Her main research topics cover different aspects of host-guest binding energy quantification, but her research interests also include the design of atomistic and coarse-grained models of polyelectrolyte systems and polymeric networks for drug delivery and removal of organic and inorganic contaminants in environmental matrices, as well as current topics that combine computational chemistry and data science methods in multivariate biochemical data processing, analysis, interpretation and prediction tasks.
Some examples include, the combination of molecular modeling and simulation methods and computational learning for the discovery of new chemical compounds, the modeling of interactions between peptides, proteins and specific ligands for the development of drugs, the classification of chemical compounds based on their molecular descriptors, fingerprints and biological activity for predicting the biological activity and toxicity of chemical compounds for identifying new pharmaceutical compounds and emerging pollutants and the optimization of critical quality attributes of pharmaceutical formulation components and critical parameters of the formulation process.
