Drug Development In Industry Research Articles

Commercially Available Cell-Free Permeability Tests for Industrial Drug Development: Increased Sustainability through Reduction of In Vivo Studies

Replacing in vivo with in vitro studies can increase sustainability in the development of medicines. This principle has already been applied in the biowaiver approach based on the biopharmaceutical classification system, BCS. A biowaiver is a regulatory process in which a drug is approved based on evidence of in vitro equivalence, i.e., a dissolution test, rather than on in vivo bioequivalence. Currently biowaivers can only be granted for highly water-soluble drugs, i.e., BCS class I/III drugs. When evaluating poorly soluble drugs, i.e., BCS class II/IV drugs, in vitro dissolution testing has proved to be inadequate for predicting in vivo drug performance due to the lack of permeability interpretation. The aim of this review was to provide solid proofs that at least two commercially available cell-free in vitro assays, namely, the parallel artificial membrane permeability assay, PAMPA, and the PermeaPad® assay, PermeaPad, in different formats and set-ups, have the potential to reduce and replace in vivo testing to some extent, thus increasing sustainability in drug development. Based on the literature review presented here, we suggest that these assays should be implemented as alternatives to (1) more energy-intense in vitro methods, e.g., refining/replacing cell-based permeability assays, and (2) in vivo studies, e.g., reducing the number of pharmacokinetic studies conducted on animals and humans. For this to happen, a new and modern legislative framework for drug approval is required.

Lessons from COVID-19 - Building a more resilient response for the next pandemic - Health System and Drug Development perspectives

This paper evaluates the challenges faced by the healthcare systems and the drug-development industry in responding to the COVID-19 pandemic. We explore the role of key stakeholders and different healthcare models that can help ensure a robust pandemic response. In drug-development, we scrutinize the challenges linked with COVID-19 antivirals, vaccines, and antibodies and explore the potential of repurposing existing therapeutics through the use of advanced technologies while predicting clinical trial outcomes. We consider the intricacies of manufacturing, regulatory, and funding factors in vaccine preparedness. We conclude by exploring the future of pandemic preparedness, highlighting rapid innovation, and the potential for accelerated drug discovery as powerful tools in addressing the next pandemic.

Multi-component Chinese medicine formulas for drug discovery: State of the art and future perspectives

For hundreds of years, the drug discovery and development industry has aimed at identifying single components with a clear mechanism of action as desirable candidates for potential drugs. However, this conventional strategy of drug discovery and development has faced challenges including a low success rate and high development costs. Herein, we critically review state-of-the-art drug discovery and development based on multi-component Chinese medicine formulas. We review the policies and application status of new drugs based on multi-component Chinese medicines in the US, China, and the European Union. Moreover, we illustrate several excellent cases of ongoing applications. Biomedical technologies that may facilitate drug discovery and development based on multi-component Chinese medicine formulas are discussed, including network pharmacology, integrative omics, CRISPR gene editing, and chemometrics. Finally, we discuss potential problems and solutions in pre-clinical and clinical research in drug discovery and development based on multi-component Chinese medicine formulas. We hope that this review will promote discussion of the roles of multi-component Chinese medicine formulas in the discovery and development of new drugs for the treatment of human diseases.

Participant recruitment and retention from vulnerable populations in clinical trials is a matter of trust

Clinical research sites can struggle with recruiting and retaining vulnerable populations. Vulnerable research participants often have significant trauma histories making traditional approaches to recruitment and retention tenuous. Due to these difficulties, vulnerable populations are often intentionally excluded from clinical research due to the additional time and work involved. While it is important to provide protections for any participant that has decreased autonomy or increased susceptibility to coercion, it is equally important to assure that individuals in vulnerable populations have access to any clinical research that might pertain to them. In addition, the new trends in the drug development industry including early-stage development, risk-identification, preventative care, and disease spread modeling are likely to include health disparate patient populations that have increased probability of vulnerability. In this article we discuss the roots of many vulnerabilities and how to foster trust for more effective recruitment and retention of vulnerable populations.

Case Study on Certara’s Simcyp PBPK Simulator to Eliminate Lengthy Clinical Trails

Background/Purpose: Analysis and new interpretation of the existing information are equivalent to creating new knowledge. A case study is an example of exploratory research and allows researchers to analyze the available information using a systematic analysis framework. In this paper, a case study on a clinical research simulation software product called Simcyp is offered by a global company Certara to its clients in the pharmaceutical industry. Objective: To know the current status of model-based drug development simulation software, with special emphasis on Certara’s Simcyp software, its features, and variations, its client’s usage pattern to prepare new drugs, its usage in research and developmental contribution during the last 22 years, and analysis of Symcyp as a research division of Certara using SWOC framework and analysis of the Symcip as simulation software using ABCD analysis framework as stakeholder analysis. Design/Methodology/Approach: The case study uses an exploratory research approach where the information is collected from various sources including the company website, its competitor’s website, various magazine articles, and scholarly articles from Google Scholar. The collected information are analyzed systematically using company analysis frameworks, product analysis framework, SWOC analysis framework, and ABCD analysis framework. Findings/Result: Based on the analysis, it is found that Symcyp is a most admired simulation software in the pharmaceutical industry for model-based drug design and development for different varieties of diseases. The strategy of Simcyp division of Certara to satisfy, delight, and enlighten its clients is also discussed. Originality/Value: The case study is based on a systematic analysis of a software product of a company using company analysis frameworks, product analysis framework, SWOC analysis framework, and ABCD analysis framework thereby contributing to interpret the existing knowledge in a new way through new interpretation. Type of Paper: Academic research based case study.

Drug allergy: A 2022 practice parameter update

Drug allergy: A 2022 practice parameter update

Utility of SPR technology in biotherapeutic development: Qualification for intended use

Surface plasmon resonance (SPR) analysis provides important binding characteristic information for an antibody to its binding partner, such as binding specificity and affinity (KD). In recent years, SPR has been increasingly used in biosimilar development as part of the comparative analytical similarity assessment. Although there is no systematic study describing how to qualify SPR assays, there are various SPR result types (outputs) that have been used for assay qualification in publicly available regulatory documents. The mixed usage of SPR output can cause confusion and can be misleading when comparing binding attributes among antibody molecules. In this report, using a recombinant huIgG1 (mAb 1) antibody as an example, we performed assay qualification strictly based on the nature of the biomolecular interaction. We recommend that KD should be used as the output of assay qualification when the KD can be measured accurately by SPR. When KD cannot be accurately determined in a SPR setting, sensorgram comparison and Parallel Line Analysis (PLA) can be used to qualify the assay. We emphasize the importance of setting up appropriate SPR assay conditions for target and/or Fc receptor interactions to ensure the assay qualification parameters, such as accuracy and repeatability, to meet the criteria acceptable for regulatory filings. With increasing numbers of biotherapeutics being developed, the methods and guidelines provided here can help to align SPR application between the drug development industry and regulatory authorities which will benefit the scientific communities involved in biotherapeutic drug development.

IMPDB: Indian Medicinal Phytochemical Database Curated for Drug Designing

Background: A paradigm shift towards a multifaceted natural product drug discovery approach has been observed globally. Today, many modern drugs have originated from ethnopharmacology and traditional medicine. The traditionally used medicinal plants are a rich source of biologically active phytochemicals. A paradigm shift has been observed in pharmaceutical industries towards the use of those phytochemicals for the development of drugs over synthetic compounds for minimization of side effects. Methodology: The data have been generated from the printed “Database on Medicinal Plants Used in Ayurveda” published by the Central Council for Research in Ayurvedic Sciences, Government of India. The curation of the phytochemicals and calculation of their physicochemical and drug-like properties has been done using Discovery Studio v 4.5, and the database IMPDB is designed by adhering to the principles of database design and developed using PHP as front-end and MySQL as back-end. The data in IMPDB were analyzed further and comparative analysis of physicochemical properties of IMPDB phytochemicals with other small molecule databases, followed by druggability and novelty analysis of phytochemicals of the database were conducted with wQED score and molecular fingerprinting methods. In addition to that, ADMET properties of IMPDB phytochemical were compared with FDA-approved drugs. Results: Druggability analysis of IMPDB phytochemical shows a substantial number of them are druggable. An extensive review of the existing database was conducted and the quality of data of existing databases was matched with IMPDB data, and IMPDB data was found at par with the standard databases in the same domain, in certain parameters the quality of data of IMPDB was found better. In addition to that, novelty analysis of IMPDB data in comparison to 2068 FDA-approved drugs reveals that 99.96–99.99% of the phytochemical of IMPDB is novel and to some extent better in terms of ADMET properties. The database is available from https://impdb.org.in/ . Conclusion: IMPDB can be a useful database for the drug development industry and a need for the future pharmaceutical industry.

Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum.

India confines more than 17% of the world’s population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population.

The implementation of a data learning series focused on clinical development teams in a contract research organization

Effective management of a clinical trial requires having real time access to information that provides useful insights into trial progress and that lends itself to collaborative decision making.  Data visualizations using data from multiple source systems employed during the conduct of a clinical trial have become an essential tool in the recent past as support for collaborative decision making by project teams. Having the ability to access, analyze, read, work with, and present data to support an argument are important skills that ensure data visualizations fulfill their purpose in clinical trial management. There is an expectation that members of the clinical trial team either possess or develop the data literacy skill sets necessary to collaborate on the successful execution of a clinical drug development trial. Here we describe the development of a Data Learning Series program targeted to increase the data literacy skills within a Contract Research Organization in support of the digital evolution of the drug development industry.

A State-of-the-Art Roadmap for Biomarker-Driven Drug Development in the Era of Personalized Therapies.

Advances in biotechnology have enabled us to assay human tissue and cells to a depth and resolution that was never possible before, redefining what we know as the “biomarker”, and how we define a “disease”. This comes along with the shift of focus from a “one-drug-fits-all” to a “personalized approach”, placing the drug development industry in a highly dynamic landscape, having to navigate such disruptive trends. In response to this, innovative clinical trial designs have been key in realizing biomarker-driven drug development. Regulatory approvals of cancer genome sequencing panels and associated targeted therapies has brought personalized medicines to the clinic. Increasing availability of sophisticated biotechnologies such as next-generation sequencing (NGS) has also led to a massive outflux of real-world genomic data. This review summarizes the current state of biomarker-driven drug development and highlights examples showing the utility and importance of the application of real-world data in the process. We also propose that all stakeholders in drug development should (1) be conscious of and efficiently utilize real-world evidence and (2) re-vamp the way the industry approaches drug development in this era of personalized medicines.

A Cross Company Perspective on the Assessment of Therapeutic Protein Biotransformation.

Unlike with new chemical entities, the biotransformation of therapeutic proteins (TPs) has not been routinely investigated or included in regulatory filings. Nevertheless, there is an expanding pool of evidence suggesting that a more in-depth understanding of biotransformation could better aid the discovery and development of increasingly diverse modalities. For instance, such biotransformation analysis of TPs affords important information on molecular stability, which in turn may shed light on any potential impact on binding affinity, potency, pharmacokinetics, efficacy, safety, or bioanalysis. This perspective summarizes the current practices in studying biotransformation of TPs and related findings in the biopharmaceutical industry. Various TP case studies are discussed, and a fit-for-purpose approach is recommended when investigating their biotransformation. In addition, we provide a decision tree to guide the biotransformation characterization for selected modalities. By raising the awareness of this important topic, which remains relatively underexplored in the development of TPs (Bolleddula et al., 2022), we hope that current and developing practices can pave the way for establishing a consensus on the biotransformation assessment of TPs. SIGNIFICANCE STATEMENT: This article provides a comprehensive perspective of the current practices for exploring the biotransformation of therapeutic proteins across the drug development industry. We, the participants of the Innovation and Quality therapeutic protein absorption distribution metabolism excretion working group, recommend and summarize appropriate approaches for conducting biotransformation studies to support internal decision making based on the data generated in discovery and development.

Ferulic acid derivatives inhibiting Staphylococcus aureus tetK and MsrA efflux pumps

Bacterial resistance to multiple drugs has recently emerged as a serious health problem. Concomitantly, the characterization of new substances with potential antimicrobial activity has been less frequent in the drug development industry. The overexpression of genes encoding efflux pumps that expel antimicrobial drugs from the intracellular environment, lowering these to subinhibitory concentrations, are among the resistance mechanisms predisposing microorganisms to high drug resistance. Staphylococcus aureus is a bacterium found in the normal microbiota of the skin and mucous membranes, and is an opportunistic microorganism capable of causing infections with high rates of morbidity and mortality. TetK is an efflux pump characterized by its ability to provide bacterial resistance to antibiotics from the tetracycline class. This study aimed to evaluate the inhibitory effect of ferulic acid and four of its esterified derivatives against resistant Staphylococcus aureus strains. Ferulic acid derivatives were obtained by esterification and then characterized by hydrogen and carbon-13 nuclear magnetic resonance analysis. The minimum inhibitory concentrations (MIC) of ferulic acid and its esterified derivatives, ethidium bromide, and antibiotics were obtained using the microdilution test, while the efflux pump inhibition test was conducted by examining reduction in the MICs. Propylferulate was seen to reduce the minimum inhibitory concentration (MIC) of both the control substance ethidium bromide and the tested antibiotic, indicating that this compound is promising for the use of efflux pump inhibition of IS-58 strains. This study provides strong evidence that the molecular basis for this activity is potentially due to the MsrA and TetK efflux pumps. However, further investigations are necessary to prove this hypothesis and elucidate the potentiating mechanism of the modulatory effect.

Academic User View: Organ-on-a-Chip Technology.

Organ-on-a-Chip (OoC) systems bring together cell biology, engineering, and material science for creating systems that recapitulate the in vivo microenvironment of tissues and organs. The versatility of OoC systems enables in vitro models for studying physiological processes, drug development, and testing in both academia and industry. This paper evaluates current platforms from the academic end-user perspective, elaborating on usability, complexity, and robustness. We surveyed 187 peers in 35 countries and grouped the responses according to preliminary knowledge and the source of the OoC systems that are used. The survey clearly shows that current commercial OoC platforms provide a substantial level of robustness and usability—which is also indicated by an increasing adaptation of the pharmaceutical industry—but a lack of complexity can challenge their use as a predictive platform. Self-made systems, on the other hand, are less robust and standardized but provide the opportunity to develop customized and more complex models, which are often needed for human disease modeling. This perspective serves as a guide for researchers in the OoC field and encourages the development of next-generation OoCs.

The Effects of Three-Dimensional Ligand Immobilization on Kinetic Measurements in Biosensors.

The field of biosensing is in constant evolution, propelled by the need for sensitive, reliable platforms that provide consistent results, especially in the drug development industry, where small molecule characterization is of uttermost relevance. Kinetic characterization of small biochemicals is particularly challenging, and has required sensor developers to find solutions to compensate for the lack of sensitivity of their instruments. In this regard, surface chemistry plays a crucial role. The ligands need to be efficiently immobilized on the sensor surface, and probe distribution, maintenance of their native structure and efficient diffusion of the analyte to the surface need to be optimized. In order to enhance the signal generated by low molecular weight targets, surface plasmon resonance sensors utilize a high density of probes on the surface by employing a thick dextran matrix, resulting in a three-dimensional, multilayer distribution of molecules. Despite increasing the binding signal, this method can generate artifacts, due to the diffusion dependence of surface binding, affecting the accuracy of measured affinity constants. On the other hand, when working with planar surface chemistries, an incredibly high sensitivity is required for low molecular weight analytes, and furthermore the standard method for immobilizing single layers of molecules based on self-assembled monolayers (SAM) of epoxysilane has been demonstrated to promote protein denaturation, thus being far from ideal. Here, we will give a concise overview of the impact of tridimensional immobilization of ligands on label-free biosensors, mostly focusing on the effect of diffusion on binding affinity constants measurements. We will comment on how multilayering of probes is certainly useful in terms of increasing the sensitivity of the sensor, but can cause steric hindrance, mass transport and other diffusion effects. On the other hand, probe monolayers on epoxysilane chemistries do not undergo diffusion effect but rather other artifacts can occur due to probe distortion. Finally, a combination of tridimensional polymeric chemistry and probe monolayer is presented and reviewed, showing advantages and disadvantages over the other two approaches.

The Degradation Map Process – A Tool for Obtaining a Lean Stability Strategy in Drug Development

Stability is fundamental when exploring a drug candidate's potential as a drug product. During the pharmaceutical industry drug development process information regarding stability and degradation are captured in different departments, e.g. from discovery to operations, and will be included in the overall control strategy. With a profound understanding of a drug candidate's degradation chemistry, a science and risk based approach in progressing a lean stability strategy is possible. This case study present a clear and visible concept to facilitate a lean stability strategy by the use of degradation maps and describes a process for how these can be used during drug development. The understanding of possible and/or observed degradation pathways will guide the design of the drug product and stability studies in development. A degradation map displays degradation pathways with short comments on the reaction/mechanism involved. The degradation map process starts with a theoretical degradation map. The map is updated as the drug project progresses, preferably after forced degradation experiments, after compatibility studies and finally when the late stage formulation is set. The degradation map should be used to capture information of intrinsic chemical properties of the active pharmaceutical ingredient (API) and can thereby be used to mitigate stability issues. The map is foremost a cross-functionally available tool collecting and visualizing stability information throughout the development process, and as such a valuable tool to efficiently develop a lean stability strategy.

Clinical development innovation in rare diseases: lessons learned and best practices from the DevelopAKUre consortium

New opportunities have arisen for development of therapies for rare diseases with the increased focus and progress in the field. However, standardised framework integrating individual initiatives has not been formed. We present lessons learned and best practice from a collaborative success case in developing a treatment for a rare genetic disease. Our unique consortium model incorporated several of the identified developments under one project, DevelopAKUre, truly bringing together academia, industry and patient organisations in clinical drug development. We found that the equal partnership between all parties in our consortium was a key success factor creating a momentum based on a strong organisational culture where all partners had high engagement and taking ownership of the entire programme. With an agreed mutual objective, this provided synergies through connecting the strengths of the individual parties. Another key success factor was the central role of the patient organisation within the management team, and their unique study participants’ advocacy role securing the understanding and meeting the needs of the clinical study participants in real-time. This resulted in an accelerated enrolment into the clinical studies with a high retention rate allowing for delivery of the programme with significantly improved timelines. Our project was partly funded through an external EU research grant, enabling our model with equal partnership. Further attention within the community should be given to establishing a functional framework where sustainable funding and risk sharing between private and public organisations allow for our model to be replicated.

Göğüs hastalıklarında yapay zeka uygulamaları ve pandemi döneminde sağladığı avantajlar

Artificial intelligence, with its increasing data volume, developing technologies, more information processing power and new algorithms, has a wide usage area in all sectors. In the field of health, these technologies is gaining an increasing place every day. Artificial intelligence methods can act as a simulation of the human mind and intelligence, resulting in the analysis and classification of complex data in a short time. Thus, by separating the small differences in the images examined, it can help diagnosis, detect preliminary signs of the disease and predict how the disease will develop. Computer based programs; diagnostic algorithms, surgical support and robotic systems developed on the basis of patient data are increasingly used in the drug development industry. In this study, artificial intelligence applications in the field of health and its use in pulmonology, the place of wearable technologies in our department and the advantages they provide us during the pandemic period were discussed in the light of the literature.

Pragmatic mAb lead molecule engineering from a developability perspective.

As the number of antibody drugs being approved and marketed increases, our knowledge of what makes potential drug candidates a successful product has increased tremendously. One of the critical parameters that have become clear in the field is the importance of mAb "developability." Efforts are being increasingly focused on simultaneously selecting molecules that exhibit both desirable biological potencies and manufacturability attributes. In the current study mutations to improve the developability profile of a problematic antibody that inconsistently precipitates in a batch scale-dependent fashion using a standard platform purification process are described. Initial bioinformatic analysis showed the molecule has no obvious sequence or structural liabilities that might lead it to precipitate. Subsequent analysis of the molecule revealed the presence of two unusual positively charged mutations on the light chain at the interface of VH and VL domains, which were hypothesized to be the primary contributor to molecule precipitation during process development. To investigate this hypothesis, straightforward reversion to the germline of these residues was carried out. The resulting mutants have improved expression titers and recovered stability within a forced precipitation assay, without any change to biological activity. Given the time pressures of drug development in industry, process optimization of the lead molecule was carried out in parallel to the "retrospective" mutagenesis approach. Bespoke process optimization for large-scale manufacturing was successful. However, we propose that such context-dependent sequence liabilities should be included in the arsenal of in silico developability screening early in development; particularly since this specific issue can be efficiently mitigated without the requirement for extensive screening of lead molecule variants.

IPO peer effects

This study investigates whether a private firm’s decision to go public affects the IPO decisions of its competitors. Using detailed data from the drug development industry, we identify a private firm’s direct competitors at a precise level through a novel approach using similarity in drug development projects based on disease targets. The analysis shows that a private firm is significantly more likely to go public after observing the recent IPO of a direct competitor, and this effect is distinct from “hot” market effects or other common shocks. Furthermore, our effects are centered on firms that operate in more competitive areas. We additionally explore peer effects in private firm funding propensities more broadly, such as through venture capital or being acquired, and find results consistent with a competitive channel.