Drug Development Teams Research Articles

Proposing a framework to quantify the potential impact of pharmacokinetic drug-drug interactions caused by a new drug candidate by using real world data about the target patient population.

Drug development teams must evaluate the risk/benefit profile of new drug candidates that perpetrate drug-drug interactions (DDIs). Real-world data (RWD) can inform this decision. The purpose of this study was to develop a predicted impact score for DDIs perpetrated by three hypothetical drug candidates via CYP3A, CYP2D6, or CYP2C9 in type 2 diabetes mellitus (T2DM), obesity, or migraine. Optum Market Clarity was analyzed to estimate use of CYP3A, CYP2D6, or CYP2C9 substrates classified in the University of Washington Drug Interaction Database as moderate sensitive, sensitive, narrow therapeutic index, or QT prolongation. Scoring was based on prevalence of exposure to victim substrates and characteristics (age, polypharmacy, duration of exposure, and number of prescribers) of those exposed. The study population of 14,163,271 adults included 1,579,054 with T2DM, 3,117,753 with obesity, and 410,436 with migraine. For T2DM, 71.3% used CYP3A substrates, 44.3% used CYP2D6 substrates, and 44.3% used CYP2C9 substrates. For obesity, 57.1% used CYP3A substrates, 34.6% used CYP2D6 substrates, and 31.0% used CYP2C9 substrates. For migraine, 64.1% used CYP3A substrates, 44.0% used CYP2D6 substrates, and 28.9% used CYP2C9 substrates. In our analyses, the predicted DDI impact scores were highest for DDIs involving CYP3A, followed by CYP2D6, and CYP2C9 substrates, and highest for T2DM, followed by migraine, and obesity. Insights from RWD can be used to estimate a predicted DDI impact score for pharmacokinetic DDIs perpetrated by new drug candidates currently in development. This score can inform the risk/benefit profile of new drug candidates in a target patient population.

Prodrugs as empowering tools in drug discovery and development: recent strategic applications of drug delivery solutions to mitigate challenges associated with lead compounds and drug candidates.

The delivery of a drug to a specific organ or tissue at an efficacious concentration is the pharmacokinetic (PK) hallmark of promoting effective pharmacological action at a target site with an acceptable safety profile. Sub-optimal pharmaceutical or ADME profiles of drug candidates, which can often be a function of inherently poor physicochemical properties, pose significant challenges to drug discovery and development teams and may contribute to high compound attrition rates. Medicinal chemists have exploited prodrugs as an informed strategy to productively enhance the profiles of new chemical entities by optimizing the physicochemical, biopharmaceutical, and pharmacokinetic properties as well as selectively delivering a molecule to the site of action as a means of addressing a range of limitations. While discovery scientists have traditionally employed prodrugs to improve solubility and membrane permeability, the growing sophistication of prodrug technologies has enabled a significant expansion of their scope and applications as an empowering tool to mitigate a broad range of drug delivery challenges. Prodrugs have emerged as successful solutions to resolve non-linear exposure, inadequate exposure to support toxicological studies, pH-dependent absorption, high pill burden, formulation challenges, lack of feasibility of developing solid and liquid dosage forms, first-pass metabolism, high dosing frequency translating to reduced patient compliance and poor site-specific drug delivery. During the period 2012-2022, the US Food and Drug Administration (FDA) approved 50 prodrugs, which amounts to 13% of approved small molecule drugs, reflecting both the importance and success of implementing prodrug approaches in the pursuit of developing safe and effective drugs to address unmet medical needs.

Making new drugs the hard way.

A new drug can have its origin in either pharma, biotech or academia. In general, discovery scientists working in pharma and biotech are advantaged over their academic counterparts and the relative advantages and disadvantages associated are discussed in depth. Against all odds, an increasing number of important drugs have had their origins in academia. This article reports three case studies from the Liotta Research Group (LRG), which explores the special circumstances that allowed these drug development campaigns to be successful. The first involves the antiretroviral agent, emtricitabine. In this case efficient synthetic methodology, developed in the LRG, coupled with some key university and commercial sector partnerships, enabled a group of academic collaborators to discover and develop a highly effective HIV reverse transcriptase inhibitor. The second case study involves the discovery and development of the breakthrough hepatitis C drug, sofosbuvir. Based on key input from Professors Schinazi and Liotta at Emory University, scientists at the Emory startup, Pharmasset, identified the nucleoside core of the drug that would become sofosbuvir. Subsequent analysis of its phosphorylation profile by Pharmasset scientists suggested that converting it to its corresponding monophosphate prodrug would circumvent a kinase block and enable it to be an effective hepatitis C polymerase inhibitor. The third case study describes the formation of DRIVE (Drug Innovation Ventures at Emory)/EIDD (Emory Institute for Drug Development), which were created to circumvent unintended impediments for carrying out academic drug discovery and development. Although DRIVE/EIDD is a wholly-owned, not-for-profit subsidiary of Emory University, it contains many attributes that enables it to operate much more nimbly than a typical academic laboratory. With an experienced drug development team and no shareholders to distract them, DRIVE/EIDD was able to focus its attention of the development of drugs to address viral diseases of global concern. In particular, their strategy to identify and develop an antiviral agent active against multiple single-stranded RNA viruses led to molnupiravir, a broadly active, oral drug that received Emergency Use Authorization for the treatment of SARS-CoV-2 infections (i.e., COVID-19).

Regulatory Status of Microbes as Antibiotics: An Overview

Regulatory affairs (RA) play crucial roles in the pharmaceutical industry because they are concerned with the lifecycle of healthcare products, they offer strategic, tactical, and operational direction, and they support working within the law to hasten the development and delivery of safe and effective healthcare products to people all over the world. The purpose of regulatory affairs is to create and implement a regulatory strategy to guarantee that the combined efforts of the drug development team result in a product that is acceptable to international regulators while also standing out from the competition. Microorganisms play a vital role in every field of drug such as production of antibiotics, antifungal, anticancer, vitamins, vaccines and enzymes etc. These are some examples where microbial products are widely used. In the present work we will discuss various aspects where microorganisms widely used in production of drug and their regulations in US and India.

Assessing adverse events in clinical trials during the era of the COVID-19 pandemic

ABSTRACT Interpretation of safety data for clinical trials that were ongoing at the onset of the COVID-19 pandemic or were started subsequent to the beginning of the pandemic may be affected in a variety of ways. Pandemic-related issues can influence the extent of study participation and introduce data collection gaps. A SARS-CoV-2 infection among study subjects as a post-randomization event may introduce a number of confounding factors that can alter the frequency of adverse events, in some cases appearing as an increase in the frequency of an adverse event associated with a study drug relative to a comparator. The authors discuss clinical challenges and statistical concerns, specifically the estimand framework, including examples for consideration, to address these challenges in safety evaluation wrought by the COVID-19 pandemic. Our aim is to shed light on the importance of starting an early dialogue among the drug development team on the evaluation of safety, critical for benefit-risk evaluation throughout the drug development process.

Estimating thermodynamic equilibrium solubility and solute–solvent interactions of niclosamide in eight mono-solvents at different temperatures

Niclosamide is an FDA-approved oral anthelmintic drug currently being repurposed for COVID-19 infection. Its interesting applicability in multiple therapeutic indications has sparked interest in this drug/ scaffold. Despite its therapeutic use for several years, its detailed solubility information from Chemistry Manufacturing & Controls perspective is unavailable. Thus, the present study is intended to determine the mole fraction solubility of niclosamide in commonly used solvents and cosolvents at a temperature range of 298.15–323.15 K. The polymorphic changes from crystalline to monohydrate forms post-equilibration in various solvents were observed. The maximum mole fraction solubility of niclosamide at 323.15 K is 1.103 × 10-3 in PEG400, followed by PEG200 (5.272 × 10-4), 1-butanol (3.047 × 10-4), 2-propanol (2.42 × 10-4), ethanol (1.66 × 10-4), DMSO (1.52 × 10-4), methanol (7.78 × 10-5) and water (3.27 × 10-7). The molecular electrostatic potential showed a linear correlation with the solubility. PEG400 has higher electrostatic potential, and H-bond acceptor count, which forms a hydrogen bond with phenolic –OH of niclosamide and thus enhances its solubility. This data is valuable for the drug discovery and development teams working on the medicinal chemistry and process chemistry of this scaffold.

Thermodynamic solubility determination of khellin in eight mono-solvents at the range of 298.15 to 323.15 K

Khellin is a medicinally important furanocoumarin class of natural product. It has led to the discovery of two first-in-class drugs, which embarks the potential of the scaffold for future research. The solubility estimation is one of the vital parameters during the preclinical development of the molecule. Thus, an objective of the present study was to determine the mole fraction solubility of khellin in eight mono-solvents at the temperature range of 298.15–323.15 K. The thermodynamic equilibrium solubility of khellin, correlated using non-linear multivariate analysis. The maximum mole fraction solubility of khellin at 323.15 K was observed as 1.525 × 10−2 in DMSO followed by 1-butanol (5.291 × 10−3), PEG 400 (5.111 × 10−3), ethanol (3.384 × 10−3), methanol (3.318 × 10−3), 2-propanol (2.533 × 10−3), PEG 200 (2.306 × 10−3) and water (9.02 × 10−5). We also studied the correlation of molecular electrostatic potential of khellin with its solubility. This data will be crucial for the drug discovery and development teams working on the medicinal chemistry of the khellin scaffold.

Regulatory Affairs in Pharmaceutical Industry

Regulatory Affairs in pharmaceutical industries is a one of the most critical job. Regulatory Affairs is mainly concerned about the lifecycle of healthcare product and it gives tactical, strategic and operation advice to work within regulation to develop safe and effective healthcare product around the World. The work of Regulatory Affairs to nurture and implementing a strategy to guarantee the collective efforts of the drug development team, so that the drug get approval from global regulatory authorities. Regulatory Affairs is a catchy career choice for graduate student from scientific background. Regulatory Affairs is a multitasking job. This job is suitable for those people who enjoys communicating with people, enjoys team work and want to expand their knowledge in pharmaceutical sector. Regulatory Affairs is a very rewarding job. A person who want pursue their job in Regulatory Affairs should have knowledge about ICH (International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use).

Enhancing the Measure of Participation Burden in Protocol Design to Incorporate Logistics, Lifestyle, and Demographic Characteristics.

Growing interest in improving patient participation convenience and the feasible execution of clinical trials has increased demand for new approaches to leverage patient input in the protocol design process. This study builds on prior work conducted by the Tufts Center for the Study of Drug Development in collaboration with ZS. A comprehensive participant burden algorithm based on protocol procedures, participation requirements and lifestyle preferences was developed and tested. Clinical trial preferences and perceptions from 3002 global patients were analyzed to inform and derive the algorithm. It was next tested against a convenience sample of 266 completed protocols. Descriptive statistics, significance tests, and regression analyses were performed. Mean participant burden scores were highly associated with, and predictive (p < 0.01) of, screen failure rates, overall clinical trial duration and the number of substantial protocol amendments; and predictive (p < 0.05) of protocol treatment duration. Of 11 subgroups assessed, those that most influenced the algorithm and drove higher overall burden scores included disease condition, caregiver reliance, race, prior experience as a clinical trial participant and participant age. Geographic area and participant sex showed only minimal influence. This study presents advancement and refinement in measuring participation burden that will assist drug development teams and protocol authors inretrospectively understanding clinical trial performance outcomes and in prospectively informing protocol design decisions.

Cooperative group and pharmaceutical sponsored clinical trials: Perceptions of U.S. community oncologists.

e13571 Background: Many community-based oncologists in the US participate in clinical trials. These trials largely fall into two categories: trials run by cooperative (co-op) groups, funded and supported by the National Cancer Institute and trials developed, and supported by the pharmaceutical (pharma) industry. This study aimed to assess participation in, and perceptions regarding, co-op versus pharma trials among US community oncologists. Methods: We invited healthcare providers (HCP) across the continental US to attend 4 virtual meetings held between September and November 2020. Participants submitted their demographic information and responses to targeted questions regarding their opinions about co-op- and pharma-sponsored trials via a web-based pre-meeting survey. We evaluated participant HCP practice demographics and survey responses using descriptive statistics. Results: Of 259 surveyed participants, HCPs specialized in hematology-oncology (57%) and medical oncology (40%) with mean (median) 19 (18) years’ clinical experience. Most HCPs (178; 69%) reported participating in clinical research, and of these, 137 (77%) participated in co-op-led and 156 (88%) participated in pharma-led clinical research. HCPs preferred participating in both pharma and co-op (49%), pharma only (22%), and co-op only (11%) trials, while 18% preferred not to participate. Co-op trials were considered more prestigious to lead (86%), less likely to imply a conflict of interest (59%), and to address more pertinent questions (58%), while pharma trials had perceived advantages of better compensation (61%) and superior efficiency (48%). Co-op trials were perceived as not being financially sustainable (69%) and slower to accrue patients (85%) than pharma-led trials. Relatedly, in a hypothetical scenario of competing trials with identical design, the majority (60%) of HCPs preferred enrolling a loved one in a co-op trial. HCPs practicing in facilities with academic affiliation (34%) and in non-academic (66%) settings reported similar perceptions about co-op- and pharma-led trials; though, HCPs in academic settings were more likely to participate in clinical research compared to those in non-academic settings (82% vs. 62% [ P=0.001], respectively). Conclusions: In our survey of experienced HCPs, co-op-led clinical trials were perceived generally more favorably than pharma-led trials, even with concerns regarding cost, feasibility, and slower recruitment. However, despite their preference for co-op trials, HCPs were more likely to participate in pharma-led trials. Almost a third of surveyed HCPs are not participating in clinical trials and a fifth do not wish to. These findings can inform stakeholders (co-op trial leadership, pharma drug development teams, and patient advocacy groups) regarding appropriate education, design, and messaging regarding future clinical trials in oncology.

Calibrating the In Vitro-In Vivo Correlation for OATP-Mediated Drug-Drug Interactions with Rosuvastatin Using Static and PBPK Models.

Organic anion-transporting polypeptide (OATP) 1B1/3-mediated drug-drug interaction (DDI) potential is evaluated in vivo with rosuvastatin (RST) as a probe substrate in clinical studies. We calibrated our assay with RST and estradiol 17-β-D-glucuronide (E217βG)/cholecystokinin-8 (CCK8) as in vitro probes for qualitative and quantitative prediction of OATP1B-mediated DDI potential for RST. In vitro OATP1B1/1B3 inhibition using E217βG and CCK8 yielded higher area under the curve (AUC) ratio (AUCR) values numerically with the static model, but all probes performed similarly from a qualitative cutoff-based prediction, as described in regulatory guidances. However, the magnitudes of DDI were not captured satisfactorily. Considering that clearance of RST is also mediated by gut breast cancer resistance protein (BCRP), inhibition of BCRP was also incorporated in the DDI prediction if the gut inhibitor concentrations were 10 × IC50 for BCRP inhibition. This combined static model closely predicted the magnitude of RST DDI with root-mean-square error values of 0.767-0.812 and 1.24-1.31 with and without BCRP inhibition, respectively, for in vitro-in vivo correlation of DDI. Physiologically based pharmacokinetic (PBPK) modeling was also used to simulate DDI between RST and rifampicin, asunaprevir, and velpatasvir. Predicted AUCR for rifampicin and asunaprevir was within 1.5-fold of that observed, whereas that for velpatasvir showed a 2-fold underprediction. Overall, the combined static model incorporating both OATP1B and BCRP inhibition provides a quick and simple mathematical approach to quantitatively predict the magnitude of transporter-mediated DDI for RST for routine application. PBPK complements the static model and provides a framework for studying molecules when a dynamic model is needed. SIGNIFICANCE STATEMENT: Using 22 drugs, we show that a static model for organic anion-transporting polypeptide (OATP) 1B1/1B3 inhibition can qualitatively predict potential for drug-drug interaction (DDI) using a cutoff-based approach, as in regulatory guidances. However, consideration of both OATP1B1/3 and gut breast cancer resistance protein inhibition provided a better prediction of the magnitude of the transporter-mediated DDI of these inhibitors with rosuvastatin. Based on these results, we have proposed an empirical mechanistic-static approach for a more reliable prediction of transporter-mediated DDI liability with rosuvastatin that drug development teams can leverage.

Sharing Data to Accelerate Medicine Development and Improve Neonatal Care: Data Standards and Harmonized Definitions

Sharing Data to Accelerate Medicine Development and Improve Neonatal Care: Data Standards and Harmonized Definitions

The Shared Ethical Responsibility of Medically and Non-medically Qualified Experts in Human Drug Development Teams.

The complexity of developing and applying increasingly sophisticated new medicinal products has led to the participation of many non-medically qualified scientists in multi-disciplinary non-clinical and clinical drug development teams world-wide. In this introductory paper to the “IFAPP International Ethics Framework for Pharmaceutical Physicians and Medicines Development Scientists” it is argued that all members of such multidisciplinary teams must share the scientific and ethical responsibilities since they all influence directly or indirectly both the outcome of the various phases of the medicines development projects and the safety of the research subjects involved. The participating medical practitioner retains the overriding responsibility and the final decision to stop a trial if the well-being of the research subjects is seriously endangered. All the team members should follow the main ethical principles governing human research, the respect for autonomy, justice, beneficence and non-maleficence. Nevertheless, the weighing of these principles might be different under various conditions according to the specialty of the members.

Managing Team Innovation in the Research and Development (R&D) Organization: Critical Determinants of Team Effectiveness.

Teams are the principal vehicle in developing new drug development strategy and executing the tasks required to accomplish those objectives. The key research questions related to the measurement of team innovation performance in the branded pharmaceutical industry and identification of the drivers for optimal team performance outcomes. This project evaluated the key drivers for team innovation performance (defined as "outcomes"). Team outcomes included new information creation, compression of development time, expansion of image, learning, capability development, growth satisfaction, and overall effectiveness. A total of 13 questions, with multiple subparts, as part of 7 key dimensions were adapted from previously validated scales. Eligible participants were those who were employed in a pharmaceutical R&D organization and were a member of a drug discovery and/or development team. Survey respondents were prompted to respond to the degree they agreed or disagreed using 5- to 7-point Likert-type scales. All analyses (reliability tests, factor analysis, and multivariate regression) were performed in IBM SPSS v22. While good correlations individually existed between team outcomes (dependent variable) and tested independent variables (autonomy, coaching, climate, proactive personality, empowering leadership, and transactive memory systems [TMSs]), the best predictors identified through multivariate regression analysis were leader and peer coaching and TMSs. This research offers key insights for managers when forming and staffing teams. One is an emphasis on coaching. It is imperative for senior managers to assign individuals to teams who liaise with broader management that are capable of offering coaching and availability for team members to enhance their skills. This is particularly important in a growing hypercompetitive environment that is witnessing continuous strategic change. A second area of emphasis is on TMS, in an expertise-centered organization. As this is a central driver to team performance, it is imperative to improve adaptation skills of team members.

Web-based Software for Real-time Simulation-assisted Trial Design in Alzheimer's Disease.

Clinical trials for Alzheimer's Disease (AD) are necessarily designed in the presence of substantial quantitative uncertainty. Certain important aspects of this uncertainty can be mitigated by developing longitudinal models for AD progression and by using these models to simulate virtual trials and estimate operating characteristics (such as statistical power, the probability of stopping at an interim analysis, the probability of identifying the correct dose, etc.) as a function of candidate design features, such as inclusion / exclusion criteria. In this brief report we describe the development and deployment of a customized software solution that allows such simulation-based results to be generated "on the fly" in the context of a drug development team meeting. This solution leverages a number of recent practical advances in statistical and scientific computing that could be much more broadly leveraged to assure more quantitatively grounded trial designs in Alzheimer's Disease.

A question-based approach to adopting pharmacogenetics to understand risk for clinical variability in pharmacokinetics in early drug development.

Understanding genetic variations that influence pharmacokinetics (PK) in humans is important for optimal clinical use of drugs. Guidances for making decisions on when to conduct pharmacogenetic research during drug development have been proposed by regulatory agencies, but their uniform adoption presents problems due to an inherent lack of flexibility. A questions-based approach (QBA) was developed to enable drug development teams at Merck to iteratively and flexibly evaluate the potential impact of pharmacogenetics (PGx) on clinical pharmacokinetic variability.

Visualization and communication of pharmacometric models with berkeley madonna.

Population or other pharmacometric models are a useful means to describe, succinctly, the relationships between drug administration, exposure (concentration), and downstream changes in pharmacodynamic (PD) biomarkers and clinical endpoints, including the mixed effects of patient factors and random interpatient variation (fixed and random effects). However, showing a set of covariate equations to a drug development team is perhaps not the best way to get a message across. Visualization of the consequences of the knowledge encapsulated within the model is the key component. Yet in many instances, it can take hours, perhaps days, to collect ideas from teams, write scripts, and run simulations before presenting the results—by which time they have moved on. How much better, then, to seize the moment and work interactively to decide on a course of action, guided by the model. We exemplify here the visualization of pharmacometric models using the Berkeley Madonna software with a particular focus on interactive sessions. The examples are provided as Supplementary Material.

Practical guidance for implementing predictive biomarkers into early phase clinical studies.

The recent U.S. Food and Drug Administration (FDA) coapprovals of several therapeutic compounds and their companion diagnostic devices (FDA News Release, 2011, 2013) to identify patients who would benefit from treatment have led to considerable interest in incorporating predictive biomarkers in clinical studies. Yet, the translation of predictive biomarkers poses unique technical, logistic, and regulatory challenges that need to be addressed by a multidisciplinary team including discovery scientists, clinicians, biomarker experts, regulatory personnel, and assay developers. These issues can be placed into four broad categories: sample collection, assay validation, sample analysis, and regulatory requirements. In this paper, we provide a primer for drug development teams who are eager to implement a predictive patient segmentation marker into an early clinical trial in a way that facilitates subsequent development of a companion diagnostic. Using examples of nucleic acid-based assays, we briefly review common issues encountered when translating a biomarker to the clinic but focus primarily on key practical issues that should be considered by clinical teams when planning to use a biomarker to balance arms of a study or to determine eligibility for a clinical study.

Conference Report: Formulating Better Medicines for Children: 4th European Paediatric Formulation Initiative Conference

The fourth annual European Paediatric Formulation Initiative (EuPFI) conference on Formulating Better Medicines for Children was held on 19-20 September 2012 at the Institute of Molecular Genetics Congress Centre, Prague, Czech Republic. The 2-day conference concentrated on the latest advances, challenges and opportunities for developing medicinal products and administration devices for pediatric use, both from European and US perspectives. It was aimed specifically at providing exposure to emerging practical applications, and for illustrating remedies utilized by pediatric drug-development teams to overcome hurdles faced in developing medicines for pediatric patients. The conference format included plenary talks, focus sessions on each of the EuPFI work streams (extemporaneous preparations, excipients, pediatric administration devices, taste masking and taste assessment, age-appropriate formulations), case studies, soapbox sessions and a parallel poster display. This conference report summarizes the keynote lectures and also gives a flavor of other presentations and posters from the conference.

Changing Routines: A Process Model of Vicarious Group Learning in Pharmaceutical R&amp;D

Prior research has indicated that groups frequently change their routines drawing on the experience of others and that this has significant performance effects. But how group routine change occurs through this process of vicarious learning is not clear. Using a qualitative field study of drug development teams in one pharmaceutical firm, I examine how groups change routines drawing on the prior related experience of other groups. An inductive analysis suggests that this process does not follow the simple find-and-copy model often assumed in the literature and identifies four distinct subprocesses involved: identification, translation, adoption, and continuation. This process model adds to understanding of vicarious learning by showing that it is a more varied process than it is commonly construed to be and that not only experience- seeking groups, but also groups that are the source of the experience, play important and shifting roles throughout. Thus, this study contributes to theories about how groups change their routines by elucidating how they alter their routines through vicarious learning.