Various Stages Of Drug Development Research Articles

Artificial intelligence for ophthalmic drug discovery and development: Capabilities, applications, and challenges

The integration of artificial intelligence (AI) into ophthalmic drug discovery and development presents transformative opportunities to address the inherent complexities and challenges of creating targeted therapies for eye diseases. The ability of AI to process vast datasets can facilitate the discovery of novel drug candidates, improve predictions of drug efficacy and safety, and streamline the drug development pipeline. Applications can range from enhancing target identification and compound screening to refining predictive toxicology. However, challenges such as data limitations, computational demands, model interpretability, and ethical considerations remain. Despite these hurdles, the integration of AI with emerging technologies and its potential to optimize clinical trials signifies a new era of innovation in ophthalmology, emphasizing its critical role in addressing current challenges and advancing therapeutic development. In this paper, we explore the role of AI in ophthalmic drug discovery, highlighting its potential to address critical challenges in the field and delineating its impact across various stages of drug development.

The Role of Patient-Reported Outcomes to Measure Treatment Satisfaction in Drug Development.

Treatment satisfaction is a person's rating of his or her treatment experience, including processes and outcomes. It is directly related to treatment adherence, which may be predictive of treatment effectiveness in clinical and real-world research. Consequently, patient-reported outcome (PRO) instruments have been developed to incorporate patient experience throughout various stages of drug development and routine care. PRO instruments enable clinicians and researchers to evaluate and compare treatment satisfaction data in different clinical settings. It is important to select fit-for-purpose PRO instruments that have demonstrated adequate levels of reliability, validity, and sensitivity to change to support their use. Some of these instruments are unidimensional while some are multidimensional; some are generic and can be applied across different therapeutic areas, while others have been developed for use in a specific treatment modality or condition. This article describes the role of treatment satisfaction in drug development as well as regulatory and Health Technology Assessment (HTA) decision making and calls for more widespread use of carefully selected treatment satisfaction PRO instruments in early- and late-phase drug development.

The Role of AI in Drug Discovery.

The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis.

Computer-aided drug design (CADD) is a drug design technique for computing ligand‒receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics. A systematic review of studies published between 2000 and July 20, 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analysed using software such as Excel, VOSviewer, RStudio, and CiteSpace. A total of 2,031 publications were included. These publications primarily originated from 99 countries or regions, led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications. Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modelling, pharmacophore modelling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics direction for future development. Furthermore, this paper will be helpful for better understanding the frontiers and hotspots of CADD.

Safety Profile of Monoclonal Antibodies and Subsequent Drug Developments in the Treatment of Paroxysmal Nocturnal Hemoglobinuria.

Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal stem cell disease characterized by intravascular hemolysis due to the targeting of affected red blood cells by the complement system. Eculizumab and ravulizumab are two monoclonal antibodies that inhibit the complement system's components and have been shown to significantly improve survival and quality of life. This review describes the role of these monoclonal antibodies in the treatment of PNH with an emphasis on their safety profile. The challenges in the use of these drugs and new drugs in various stages of drug development are also described, which may be helpful in addressing some of these challenges.

CETSA and thermal proteome profiling strategies for target identification and drug discovery of natural products

BackgroundMonitoring target engagement at various stages of drug development is essential for natural product (NP)-based drug discovery and development. The cellular thermal shift assay (CETSA) developed in 2013 is a novel, broadly applicable, label-free biophysical assay based on the principle of ligand-induced thermal stabilization of target proteins, which enables direct assessment of drug-target engagement in physiologically relevant contexts, including intact cells, cell lysates and tissues. This review aims to provide an overview of the work principles of CETSA and its derivative strategies and their recent progress in protein target validation, target identification and drug lead discovery of NPs. MethodsA literature-based survey was conducted using the Web of Science and PubMed databases. The required information was reviewed and discussed to highlight the important role of CETSA-derived strategies in NP studies. ResultsAfter nearly ten years of upgrading and evolution, CETSA has been mainly developed into three formats: classic Western blotting (WB)-CETSA for target validation, thermal proteome profiling (TPP, also known as MS-CETSA) for unbiased proteome-wide target identification, and high-throughput (HT)-CETSA for drug hit discovery and lead optimization. Importantly, the application possibilities of a variety of TPP approaches for the target discovery of bioactive NPs are highlighted and discussed, including TPP-temperature range (TPP-TR), TPP-compound concentration range (TPP-CCR), two-dimensional TPP (2D-TPP), cell surface-TPP (CS-TPP), simplified TPP (STPP), thermal stability shift-based fluorescence difference in 2D gel electrophoresis (TS-FITGE) and precipitate supported TPP (PSTPP). In addition, the key advantages, limitations and future outlook of CETSA strategies for NP studies are discussed. ConclusionThe accumulation of CETSA-based data can significantly accelerate the elucidation of the mechanism of action and drug lead discovery of NPs, and provide strong evidence for NP treatment against certain diseases. The CETSA strategy will certainly bring a great return far beyond the initial investment and open up more possibilities for future NP-based drug research and development.

Drug reprofiling history and potential therapies against Parkinson's disease.

Given the high whittling down rates, high costs, and moderate pace of new medication, revelation, and improvement, repurposing "old" drugs to treat typical and uncommon illnesses is progressively becoming an appealing proposition. Drug repurposing is the way toward utilizing existing medications in treating diseases other than the purposes they were initially designed for. Faced with scientific and economic challenges, the prospect of discovering new medication indications is enticing to the pharmaceutical sector. Medication repurposing can be used at various stages of drug development, although it has shown to be most promising when the drug has previously been tested for safety. We describe strategies of drug repurposing for Parkinson's disease, which is a neurodegenerative condition that primarily affects dopaminergic neurons in the substantia nigra. We also discuss the obstacles faced by the repurposing community and suggest new approaches to solve these challenges so that medicine repurposing can reach its full potential.

Therapeutic drug repositioning with special emphasis on neurodegenerative diseases: Threats and issues.

Drug repositioning or repurposing is the process of discovering leading-edge indications for authorized or declined/abandoned molecules for use in different diseases. This approach revitalizes the traditional drug discovery method by revealing new therapeutic applications for existing drugs. There are numerous studies available that highlight the triumph of several drugs as repurposed therapeutics. For example, sildenafil to aspirin, thalidomide to adalimumab, and so on. Millions of people worldwide are affected by neurodegenerative diseases. According to a 2021 report, the Alzheimer’s disease Association estimates that 6.2 million Americans are detected with Alzheimer’s disease. By 2030, approximately 1.2 million people in the United States possibly acquire Parkinson’s disease. Drugs that act on a single molecular target benefit people suffering from neurodegenerative diseases. Current pharmacological approaches, on the other hand, are constrained in their capacity to unquestionably alter the course of the disease and provide patients with inadequate and momentary benefits. Drug repositioning–based approaches appear to be very pertinent, expense- and time-reducing strategies for the enhancement of medicinal opportunities for such diseases in the current era. Kinase inhibitors, for example, which were developed for various oncology indications, demonstrated significant neuroprotective effects in neurodegenerative diseases. This review expounds on the classical and recent examples of drug repositioning at various stages of drug development, with a special focus on neurodegenerative disorders and the aspects of threats and issues viz. the regulatory, scientific, and economic aspects.

Pros and cons of NRF2 activation as adjunctive therapy in rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease with an important inflammatory component accompanied by deregulated redox-dependent signaling pathways that are feeding back into inflammation. In this context, we bring into focus the transcription factor NRF2, a master redox regulator that exerts exquisite antioxidant and anti-inflammatory effects. The review does not intend to be exhaustive, but to point out arguments sustaining the rationale for applying an NRF2-directed co-treatment in RA as well as its potential limitations. The involvement of NRF2 in RA is emphasized through an analysis of publicly available transcriptomic data on NRF2 target genes and the findings from NRF2-knockout mice. The impact of NRF2 on concurrent pathologic mechanisms in RA is explained by its crosstalk with major redox-sensitive inflammatory and cell death-related pathways, in the context of the increased survival of pathologic cells in RA. The proposed adjunctive therapy targeted to NRF2 is further sustained by the existence of promising NRF2 activators that are in various stages of drug development. The interference of NRF2 with conventional anti-rheumatic therapies is discussed, including the cytoprotective effects of NRF2 for alleviating drug toxicity. From another perspective, the review presents how NRF2 activation would be decreasing the efficacy of synthetic anti-rheumatic drugs by increasing drug efflux. Future perspectives regarding pharmacologic NRF2 activation in RA are finally proposed.

The Relevance of Crystal Forms in the Pharmaceutical Field: Sword of Damocles or Innovation Tools?

This review is aimed to provide to an “educated but non-expert” readership and an overview of the scientific, commercial, and ethical importance of investigating the crystalline forms (polymorphs, hydrates, and co-crystals) of active pharmaceutical ingredients (API). The existence of multiple crystal forms of an API is relevant not only for the selection of the best solid material to carry through the various stages of drug development, including the choice of dosage and of excipients suitable for drug development and marketing, but also in terms of intellectual property protection and/or extension. This is because the physico-chemical properties, such as solubility, dissolution rate, thermal stability, processability, etc., of the solid API may depend, sometimes dramatically, on the crystal form, with important implications on the drug’s ultimate efficacy. This review will recount how the scientific community and the pharmaceutical industry learned from the catastrophic consequences of the appearance of new, more stable, and unsuspected crystal forms. The relevant aspects of hydrates, the most common pharmaceutical solid solvates, and of co-crystals, the association of two or more solid components in the same crystalline materials, will also be discussed. Examples will be provided of how to tackle multiple crystal forms with screening protocols and theoretical approaches, and ultimately how to turn into discovery and innovation the purposed preparation of new crystalline forms of an API.

Current practices for QSP model assessment: an IQ consortium survey.

Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10928-022-09811-1.

Bioanalytical Method Development and Validation for the Estimation of Saxagliptin in Marketed Tablet Formulation

The concepts, importance and application of bioanalytical method development have been discussed for a long time and validation of bioanalytical methods is widely accepted as pivotal before they are taken into routine use. Now it is widely accepted that bioanalysis is an integral part of the clinical diagnosis, biomarker discovery, pharmacokinetic/ pharmacodynamic characterization of a novel chemical entity from the time of its discovery and during various stages of drug development, leading to its market authorization. Bioanalytical methods, based on a variety of physico-chemical and biological techniques such as chromatography, immunoassay and mass spectrometry, must be validated prior to and during use to give confidence in the results generated. This study describes the development of an innovative, rapid, precise, selective and sensitive reverse phase high-performance liquid chromatography method for the quantitative determination of Saxagliptin (SAXA) in human plasma and pharmaceutical dosage form. Extraction of drug from plasma was done by employing optimized liquid-liquid extraction procedure. The sample was analyzed using methanol: acetonitrile in the ratio of 50:50v/v as mobile phase. Chromatographic separation was achieved on Thermo C18 analytical column (250mm×4.6mm i.d., 5.0μm) as stationary phase using isocratic elution (at a flow rate of 1 ml/min). The peak was detected using UV-PDA detector set at 230 nm and the total time for a chromatographic separation was 20 min. The calibration curve obtained was linear (r2 = 0.999) over the concentration range of 5-25μg/ml for SAXA. Method was validated for precision, robustness and recovery.

Model-Informed Drug Development Approaches to Assist New Drug Development in the COVID-19 Pandemic.

Leveraging limited clinical and nonclinical data through modeling approaches facilitates new drug development and regulatory decision making amid the coronavirus disease 2019 (COVID‐19) pandemic. Model‐informed drug development (MIDD) is an essential tool to integrate those data and generate evidence to (i) provide support for effectiveness in repurposed or new compounds to combat COVID‐19 and dose selection when clinical data are lacking; (ii) assess efficacy under practical situations such as dose reduction to overcome supply issues or emergence of resistant variant strains; (iii) demonstrate applicability of MIDD for full extrapolation to adolescents and sometimes to young pediatric patients; and (iv) evaluate the appropriateness for prolonging a dosing interval to reduce the frequency of hospital visits during the pandemic. Ongoing research activities of MIDD reflect our continuous effort and commitment in bridging knowledge gaps that leads to the availability of effective treatments through innovation. Case examples are presented to illustrate how MIDD has been used in various stages of drug development and has the potential to inform regulatory decision making.

Flow cytometry and pharmacokinetics.

Multiparametric flow cytometry is a powerful cellular analysis tool used in various stages of drug development. In adoptive cell therapies, the flow cytometry methods are used for the evaluation of advanced cellular products during manufacturing and to monitor cellular kinetics after infusion. In this report, we discussed the bioanalytical method development challenges to monitor cellular kinetics in CAR-T cell therapies. These method development challenges include procuring positive control samples for the development of the method, flow cytometry panel design, LLOQ, prestain sample stability, staining reagents and data analysis.

Inhibitory Potential of Dietary Nutraceuticals on Cellular PI3K/Akt Signaling: Implications in Cancer Prevention and Therapy.

The phosphatidyl inositol-3 kinase (PI3K)/protein kinase B (Akt)/mechanistic target of rapamycin (mTOR) signaling has been associated with many cellular physiological events, such as proliferation, maturation, survival, and metabolism. Besides its role in normal cells, the pathway is often upregulated in various cancers. Due to its prominent role in the cancer progression events, it is now being considered as a target for cancer therapy and cancer chemoprevention. The present review provides a concise outline of the role of the PI3K/Akt/mTOR pathway in carcinogenesis and progression events, including metastasis, drug resistance and stemness. Further, emphasis needs to be placed on the PI3K/Akt/mTOR pathway inhibitory potentials of various food-derived bioactive components in cancer prevention. Data on the PI3K/Akt/mTOR inhibiting natural products and their bioactive compounds have been obtained from PubMed/Medline, Scopus, Eurekaselect, etc. Findings from the above citation databases from 2000-2021 are included in the manuscript. Numerous compounds from plants have been isolated and identified as anticancer agents; among these, a predominant class is nutraceuticals. The PI3K pathway is the predominant target of these natural products, and many of these drug candidates are under various stages of drug development. These compounds have shown a significant inhibitory effect on the kinase activities of PI3K and Akt, resulting in the abrogation of cancer initiation and progression events. In addition, these compounds have been shown to reverse the resistance to chemotherapeutic drugs and also reduce the population of cancer stem cells. The nutraceuticals are promising candidates as anticancer agents by blocking PI3K signaling cascades. As the PI3K is a central pathway to various receptors signaling, the dietary intervention may prove to be highly effective.

Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate.

As model‐informed drug development becomes an integral part of modern approaches to the discovery of new therapeutic entities and showing their safety and effectiveness, modalities of incorporating the paradigm into widespread practice require a revisit. Traditionally, modeling and simulation (M&S) have been performed by specialized teams who create bespoke models for each case and have reservations about letting modeling be done by the greater mass of scientists engaged in various stages of drug development. An analogy can be drawn between M&S and automobiles: typical drivers of ordinary cars use them for daily tasks, such as going from point A to B whereas specialized Formula 1 drivers using bespoke individually made cars to test the latest technologies. The reliability and robustness of ordinary cars for the first group requires elements related to quality and endurance that are very different from those applicable to any Formula 1 car supported by a large team of engineers. In this commentary, we frame and analyze the problems concerning the structure and setup of various M&S tools, and their pros and cons. We demonstrate that many misconceptions have precluded having an open discussion on what each modality of M&S tools strives to achieve, and we provide data and evidence that support the move of M&S to main stream use by many, as opposed to specialized usage by few. Parallels are drawn in many other areas involving laboratory instrumentation, statistical analyses, and so on.

Pivotal Role of Translation in Anti-Infective Development.

The value of model-based translation in drug discovery and development is now effectively being recognized in many disease areas and among various stakeholders. Such quantitative approaches are expected to facilitate the selection on which compound to prioritize for successful development, predict the human efficacious dose based on preclinical data with adequate precision, guide design, and de-risk later development stages. The importance of time-dependencies, which are typically species-dependent due to different turnover rates of biological processes, is, however, often neglected. For bacterial infections, the choice of dosing regimen is typically relying on preclinical pharmacokinetic (PK) and pharmacodynamic (PD) data, because the bacterial load and disease severity, and consequently the PK/PD relationship, cannot be quantified well on clinical data, given the low-information end points used. It is time to recognize the limitations of using time-collapsed approaches for translation (i.e., methods where targets are based on summary measures of exposure and response). Models describing the full time-course captures important quantitative information of drug distribution, bacterial growth, antibiotic killing, and resistance development, and can account for species-differences in the PK profiles driving the killing. Furthermore, with a model-based approach for translation, we can take a holistic approach in development of a joint model for in vitro, in vivo, and clinical data, as well as incorporating information on the contribution of the immune system. Such advancements are anticipated to facilitate rational decision making during various stages of drug development and in the optimization of treatment regimens for different groups of patients.

Recent Advances on Epidermal Growth Factor Receptor as a Molecular Target for Breast Cancer Therapeutics.

Epidermal Growth Factor Receptor (EGFR), a type-I transmembrane protein with intrinsic tyrosine kinase activity, is activated by peptide growth factors such as EGF, epigen, amphiregulin, etc. EGFR plays a vital role in regulating cell growth, migration, and differentiation in various tissue-specific cancers. It has been reported to be overexpressed in lung, head, and neck, colon, brain, pancreatic, and breast cancer that triggers tumor progression and drug resistance. EGFR overexpression alters the signaling pathway and induces cell division, invasion, and cell survival. Our prior studies demonstrated that EGFR inhibition modulates chemosensitivity in breast cancer stem cells, thereby serving as a potential drug target for breast cancer mitigation. Tyrosine kinase inhibitors (Lapatinib, Neratinib) and monoclonal antibodies (Trastuzumab) targeting EGFR have been developed and approved by the US FDA for clinical use against breast cancer. This review highlights the critical role of EGFR in breast cancer progression and enumerates the various approaches being undertaken to inhibit aggressive breast cancers by suppressing the downstream pathways. Furthermore, the mechanisms of action of potential molecules at various stages of drug development, as well as clinically approved drugs for breast cancer treatment, are illustrated.

Herbal Antimycotics and Their Prospects in Therapeutics

Herbal antimycotics are being researched as antimicrobials to treat antibiotic-resistant fungal infections and as food preservatives (against food spoilage and mycotoxigenic fungi). Several antimycotic herbal compounds including cinnamaldehyde (in cinnamon, camphor, and cassia oils), carvacrol (in oregano, thyme, thymus and ajowan oils) and citral (in lemongrass, verbena, and citronella oils) inhibit yeasts and molds in microgram concentration. Their therapeutic use is still limited because of several biological, chemical, and pharmaceutical reasons. The dearth of long-term toxicity studies, pharmacodynamics and pharmacokinetics data, verifiable clinical trials data (at various stages of drug development), quality control, standard testing and preparation protocols, reference values and pharmacopoeia. Thus, proclaiming herbal antimycotics as future drugs either as an alternative or as a complementary therapeutic agent is still farfetched dream to come true.

Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities

Quantitative systems pharmacology (QSP) approaches have been increasingly applied in the pharmaceutical since the landmark white paper published in 2011 by a National Institutes of Health working group brought attention to the discipline. In this perspective, we discuss QSP in the context of other modeling approaches and highlight the impact of QSP across various stages of drug development and therapeutic areas. We discuss challenges to the field as well as future opportunities.