Accelerating drug development at Bristol Myers Squibb through innovation.

This paper focuses on the use of novel technologies and innovative trial designs to accelerate evidence generation and increase pharmaceutical Research and Development (R&D) productivity, at Bristol Myers Squibb. We summarize learnings with case examples, on how we prepared and continuously evolved to address the increasing cost, complexities, and external pressures in drug development, to bring innovative medicines to patients much faster. These learnings were based on review of internal efforts toward accelerating R&D focusing on four key areas: adopting innovative trial designs, optimizing trial designs, leveraging external control data, and implementing novel methods using artificial intelligence and machine learning.

Using automated patch clamp electrophysiology platforms in ion channel drug discovery: an industry perspective.

INTRODUCTION: Automated patch clamp (APC) is now well established as a mature technology for ion channel drug discovery in academia, biotech and pharma companies, and in contract research organizations (CRO), for a variety of applications including channelopathy research, compound screening, target validation and cardiac safety testing. AREAS COVERED: Ion channels are an important class of drugged and approved drug targets. The authors present a review of the current state of ion channel drug discovery along with new and exciting developments in ion channel research involving APC. This includes topics such as native and iPSC-derived cells in ion channel drug discovery, channelopathy research, organellar and biologics in ion channel drug discovery. EXPERT OPINION: It is our belief that APC will continue to play a critical role in ion channel drug discovery, not only in 'classical' hit screening, target validation and cardiac safety testing, but extending these applications to include high throughput organellar recordings and optogenetics. In this way, with advancements in APC capabilities and applications, together with high resolution cryo-EM structures, ion channel drug discovery will be re-invigorated, leading to a growing list of ion channel ligands in clinical development.

Patient-centric Comparability Assessment of Biopharmaceuticals.

The comparability assessment of a biological product after implementing a manufacturing process change should involve a risk-based approach. Process changes may occur at any stage of the product lifecycle: early development, clinical manufacture for pivotal trials, or post-approval. The risk of the change to impact product quality varies. The design of the comparability assessment should be adapted accordingly. A working group reviewed and consolidated industry approaches to assess comparability of traditional protein-based biological products during clinical development and post-approval. The insights compiled in this review article encompass topics such as a risk-evaluation strategy, the design of comparability studies, definition of assessment criteria for comparability, holistic evaluation of data, and the regulatory submission strategy. These practices can be leveraged across the industry to help companies in design and execution of comparability assessments, and to inform discussions with global regulators.

VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search.

Molecular generation is crucial for advancing drug discovery, materials science, and chemical exploration. It expedites the search for new drug candidates, facilitates tailored material creation, and enhances our understanding of molecular diversity. By employing artificial intelligence techniques such as molecular generative models based on molecular graphs, researchers have tackled the challenge of identifying efficient molecules with desired properties. Here, we propose a new molecular generative model combining a graph-based deep neural network and a reinforcement learning technique. We evaluated the validity, novelty, and optimized physicochemical properties of the generated molecules. Importantly, the model explored uncharted regions of chemical space, allowing for the efficient discovery and design of new molecules. This innovative approach has considerable potential to revolutionize drug discovery, materials science, and chemical research for accelerating scientific innovation. By leveraging advanced techniques and exploring previously unexplored chemical spaces, this study offers promising prospects for the efficient discovery and design of new molecules in the field of drug development.

Current State and Challenges of Physiologically Based Biopharmaceutics Modeling (PBBM) in Oral Drug Product Development.

Physiologically based biopharmaceutics modeling (PBBM) emphasizes the integration of physicochemical properties of drug substance and formulation characteristics with system physiological parameters to predict the absorption and pharmacokinetics (PK) of a drug product. PBBM has been successfully utilized in drug development from discovery to postapproval stages and covers a variety of applications. The use of PBBM facilitates drug development and can reduce the number of preclinical and clinical studies. In this review, we summarized the major applications of PBBM, which are classified into six categories: formulation selection and development, biopredictive dissolution method development, biopharmaceutics risk assessment, clinically relevant specification settings, food effect evaluation and pH-dependent drug-drug-interaction risk assessment. The current state of PBBM applications is illustrated with examples from published studies for each category of application. Despite the variety of PBBM applications, there are still many hurdles limiting the use of PBBM in drug development, that are associated with the complexity of gastrointestinal and human physiology, the knowledge gap between the in vitro and the in vivo behavior of drug products, the limitations of model interfaces, and the lack of agreed model validation criteria, among other issues. The challenges and essential considerations related to the use of PBBM are discussed in a question-based format along with the scientific thinking on future research directions. We hope this review can foster open discussions between the pharmaceutical industry and regulatory agencies and encourage collaborative research to fill the gaps, with the ultimate goal to maximize the applications of PBBM in oral drug product development.

Towards Pharma 4.0 in clinical trials: A future-orientated perspective.

Pharma 4.0, a technology ecosystem in drug development analogous to Industry 4.0 in healthcare, is transforming the traditional approach to drug discovery and development, aligning product quality with less time to market, and creating intelligent stakeholder networks through effective collaborations. The wide range of potential Pharma 4.0 networks have produced several conceptualizations, which have led to a lack of clarity and definition. The main emphasis of this paper is on the clinical trial stage of drug development in the Pharma 4.0 era. It highlights the merged computerized technologies that are currently used in clinical research, and proposes a framework for integrating Pharma 4.0 technologies. The impact of and barriers to employing the proposed framework are discussed, highlighting its potential and some future research applications.

Combining repurposed drugs to treat colorectal cancer.

The drug development process, especially of antineoplastic agents, has become increasingly costly and ineffective. Drug repurposing and drug combination are alternatives to de novo drug development, being low cost, rapid, and easy to apply. These strategies allow higher efficacy, decreased toxicity, and overcoming of drug resistance. The combination of antineoplastic agents is already being applied in cancer therapy, but the combination of repurposed drugs is still under-explored in pre- and clinical development. In this review, we provide a set of pharmacological concepts focusing on drug repurposing for treating colorectal cancer (CRC) and that are relevant for the application of new drug combinations against this disease.

Building HTA insights into the drug development plan: Current approaches to seeking early scientific advice from HTA agencies.

There is a growing trend for pharmaceutical companies to seek scientific advice on drug development from a Health Technology Assessment (HTA) perspective, to improve the efficiency of their studies, enable better trial design, and support the goals of positive HTA recommendation for reimbursement. This study uses information collected directly from companies on individual products to assess their strategies and practices for seeking HTA-related scientific advice in terms of which stakeholders to engage and for what purpose, when to seek scientific advice, and whether to implement that advice within global clinical development.

Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.

Interest in real-world data (RWD) and real-world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third-party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single-arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness "big" RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient-derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.

Improving the assessment of the probability of success in late stage drug development.

There are several steps to confirming the safety and efficacy of a new medicine. A sequence of trials, each with its own objectives, is usually required. Quantitative risk metrics can be useful for informing decisions about whether a medicine should transition from one stage of development to the next. To obtain an estimate of the probability of regulatory approval, pharmaceutical companies may start with industry-wide success rates and then apply to these subjective adjustments to reflect program-specific information. However, this approach lacks transparency and fails to make full use of data from previous clinical trials. We describe a quantitative Bayesian approach for calculating the probability of success (PoS) at the end of phase II which incorporates internal clinical data from one or more phase IIb studies, industry-wide success rates, and expert opinion or external data if needed. Using an example, we illustrate how PoS can be calculated accounting for differences between the phase II data and future phase III trials, and discuss how the methods can be extended to accommodate accelerated drug development pathways.

Pharmaceutical drug development: high drug prices and the hidden role of public funding.

In 2019, the record for the most expensive drug was broken at US$2.1 million per patient. The high costs of new drugs are justified by the pharmaceutical industry as the expense required for maintaining research and development (R&D) pipelines. However, this does not take into account that globally the public pays for between one to two-thirds of upfront R&D costs through taxpayers or charitable donations. Governments are effectively paying twice for medicines; first through R&D, and then paying the high prices upon approval. High drug prices distort research priorities, emphasising financial gains and not health gains. In this manuscript, issues surrounding the current patent-based drug development model, public funding of research and pharmaceutical lobbying will be addressed. Finally, innovations in drug development to improve public health needs and guaranteeing medication access to patients will be explored.

HLM-beads: Rapid Assessment of Nonspecific Binding to Human Liver Microsomes Using Magnetizable Beads.

In early drug development, drug-drug interaction risk is routinely assessed using human liver microsomes (HLMs). Nonspecific binding of drugs to HLMs can affect the determination of accurate enzyme parameters (Km, Ki, KI). Previously, we described a novel in vitro model consisting of HLMs bound to magnetizable beads [HLM-magnetizable-beads system (HLM-beads)]. The HLM-beads enable rapid separation of HLMs from incubation media by applying a magnetic field. Here, HLM-beads were further characterized and evaluated as a tool to assess HLM nonspecific binding of small molecules. The free fractions (fu,mic) of 13 compounds (chosen based on their pKa values) were determined using HLM-beads under three HLM concentrations (0.025, 0.50, and 1.0 mg/ml) and compared with those determined by equilibrium dialysis. Most fu,mic values obtained using HLM-beads were within 0.5- to 2-fold of the values determined using equilibrium dialysis. The highest fold difference were observed for high binders itraconazole and BIRT2584 (1.9- to 2.9-fold), as the pronounced adsorption of these compounds to the equilibrium dialysis apparatus interfered with their fu,mic determination. Correlation and linear regression analysis of the fu,mic values generated using HLM-beads and equilibrium dialysis was conducted. Overall, a good correlation of fu,mic values obtained by the two methods were observed, as the r and R2 values from correlational analysis and linear regression analysis were >0.9 and >0.89, respectively. These studies demonstrate that HLM-beads can produce comparable fu,mic values as determined by equilibrium dialysis while reducing the time required for this type of study from hours to only 10 minutes and compound apparatus adsorption. SIGNIFICANCE STATEMENT: This work introduces a new method of rapidly assessing nonspecific microsomal binding using human liver microsomes bound to magnetizable beads.

Genotoxicity test battery - An assessment of its utility in early drug development.

Formal requirements for genotoxicity testing of drug candidates to support clinical entry have been in place since the issue of initial regulatory guidance over 25 years ago and subsequent update a decade ago. An evaluation of such testing, supporting first clinical entry of 108 small molecule drug candidates over the last decade, showed that the most common approach (75 % of tested compounds) was for a Good Laboratory Practice test battery in the form of 2 in vitro (a bacterial reverse mutation and a mammalian cell) assays and one in vivo assay. The majority of other tested compounds involved in vitro testing only in bacterial reverse mutation and mammalian cell assays. Testing using a bacterial reverse mutation assay and an in vivo assessment of genotoxicity with 2 different tissues was limited to 2 occasions. For in vitro mammalian cell testing, the chromosome aberration test was most commonly used (70 % occasions), followed by a micronucleus test (16 % occasions) or a mouse lymphoma assay (14 % occasions). For in vivo evaluation, the most common test was a rodent bone marrow micronucleus test (87 % occasions). A positive in vitro mammalian cell assay result was seen on 13 % occasions but was not confirmed with further in vivo testing and the drug candidates were taken into the clinic. In conclusion, the present evaluation showed that the current test battery paradigm for genotoxicity testing has an integral part in supporting clinical entry to confirm candidate drugs taken into the clinic are unlikely to have genotoxic activity.

Amoxicillin chewable tablets intended for pediatric use: formulation development, stability evaluation and taste assessment.

To cover the unpleasant taste of amoxicillin (250 mg), maize starch (baby food) and milk chocolate were co-formulated. The raw materials and the final formulations were characterized by means of Dynamic Light Scattering (DLS), Differential Scanning Calorimetry (DSC) and Fourier-Transform Infrared (FT-IR) spectroscopy. To evaluate the taste masking two different groups of volunteers were used, according to the Ethical Research Committee of the Aristotle University of Thessaloniki. The optimization of excipients' content in the tablet was determined by experimental design methodology (crossed D-optimal). Due to the matrix complexity, amoxicillin was extracted using liquid extraction and analyzed isocratically by HPLC. The developed chromatographic method was validated (%Recovery 98.7-101.3, %RSD = 1.3, LOD and LOQ 0.15 and 0.45 µg mL-1 respectively) according to the International Conference on Harmonization (ICH) guidelines. The physicochemical properties of the tablets were also examined demonstrating satisfactory quality characteristics (diameter: 15 mm, thickness: 6 mm, hardness <98 Newton, loss of mass <1.0%, disintegration time ∼25min). Additionally, dissolution (%Recovery >90) and in vitro digestion tests (%Recovery >95) were carried out. Stability experiments indicated that amoxicillin is stable in the prepared formulations for at least one year (%Recovery <91).

Systematic risk identification and assessment using a new risk map in pharmaceutical R&D.

Delivering transformative therapies to patients while maintaining growth in the pharmaceutical industry requires an efficient use of research and development (R&D) resources and technologies to develop high-impact new molecular entities (NMEs). However, increasing global R&D competition in the pharmaceutical industry, growing impact of generics and biosimilars, more stringent regulatory requirements, as well as cost-constrained reimbursement frameworks challenge current business models of leading pharmaceutical companies. Big data-based analytics and artificial intelligence (AI) approaches have disrupted various industries and are having an increasing impact in the biopharmaceutical industry, with the promise to improve and accelerate biopharmaceutical R&D processes. Here, we systematically analyze, identify, assess, and categorize key risks across the drug discovery and development value chain using a new risk map approach, providing a comprehensive risk-reward analysis for pharmaceutical R&D.

Responsible use of negative research outcomes-accelerating the discovery and development of new antibiotics.

Failure to share and make use of existing knowledge, particularly negative research outcomes, has been recognized as one of the key sources of waste and inefficiency in the drug discovery and development process. In the field of antibiotic research, providing a platform where negative outcomes could be shared to prevent the vicious cycle of duplicating costly studies that produce the same negative results would greatly de-risk and accelerate the development of new antibiotics. Providing a legally supported framework that recognizes negative outcomes as intellectual contributions, which can subsequently be translated into a revenue-sharing model, may lead to more openness and value creation in support of a sustainable and responsible transformation of research into socially and economically beneficial innovations.