Into the valley of death: research to innovation

Advances in non-hormonal male contraception targeting sperm motility

BACKGROUND

The high rates of unintended pregnancy and the ever-growing world population impose health, economic, social, and environmental threats to countries. Expanding contraceptive options, including male methods, are urgently needed to tackle these global challenges. Male contraception is limited to condoms and vasectomy, which are unsuitable for many couples. Thus, novel male contraceptive methods may reduce unintended pregnancies, meet the contraceptive needs of couples, and foster gender equality in carrying the contraceptive burden. In this regard, the spermatozoon emerges as a source of druggable targets for on-demand, non-hormonal male contraception based on disrupting sperm motility or fertilization.

OBJECTIVE AND RATIONALE

A better understanding of the molecules governing sperm motility can lead to innovative approaches toward safe and effective male contraceptives. This review discusses cutting-edge knowledge on sperm-specific targets for male contraception, focusing on those with crucial roles in sperm motility. We also highlight challenges and opportunities in male contraceptive drug development targeting spermatozoa.

SEARCH METHODS

We conducted a literature search in the PubMed database using the following keywords: 'spermatozoa', 'sperm motility', 'male contraception', and 'drug targets' in combination with other related terms to the field. Publications until January 2023 written in English were considered.

OUTCOMES

Efforts for developing non-hormonal strategies for male contraception resulted in the identification of candidates specifically expressed or enriched in spermatozoa, including enzymes (PP1γ2, GAPDHS, and sAC), ion channels (CatSper and KSper), transmembrane transporters (sNHE, SLC26A8, and ATP1A4), and surface proteins (EPPIN). These targets are usually located in the sperm flagellum. Their indispensable roles in sperm motility and male fertility were confirmed by genetic or immunological approaches using animal models and gene mutations associated with male infertility due to sperm defects in humans. Their druggability was demonstrated by the identification of drug-like small organic ligands displaying spermiostatic activity in preclinical trials.

WIDER IMPLICATIONS

A wide range of sperm-associated proteins has arisen as key regulators of sperm motility, providing compelling druggable candidates for male contraception. Nevertheless, no pharmacological agent has reached clinical developmental stages. One reason is the slow progress in translating the preclinical and drug discovery findings into a drug-like candidate adequate for clinical development. Thus, intense collaboration among academia, private sectors, governments, and regulatory agencies will be crucial to combine expertise for the development of male contraceptives targeting sperm function by (i) improving target structural characterization and the design of highly selective ligands, (ii) conducting long-term preclinical safety, efficacy, and reversibility evaluation, and (iii) establishing rigorous guidelines and endpoints for clinical trials and regulatory evaluation, thus allowing their testing in humans.

Development of medicines for rare diseases and inborn errors of metabolism: Toward novel public-private partnerships

Medicine development for rare diseases, including inborn errors of metabolism (IEMs) is challenging. Many academic innovations fail to reach the patient, either by stranding in the translational stage or due to suboptimal patient access related to pricing or uncertain effectiveness. Expanding and solidifying the role of the academic in public-private partnerships (PPPs) may present an innovative solution to help overcome these complexities. This narrative review explores the literature on traditional and novel collaborative approaches to medicine development for rare diseases and analyzes examples of PPPs, with a specific focus on IEMs. Several academic institutions have introduced guidelines for socially responsible licensing of innovations for private development. The PPP model offers a more integrative approach toward academic involvement of medicine development. By sharing risks and rewards, failures in the translational stage can be mutually absorbed. If socially responsible terms are not included, however, high pricing can impede patient access. Therefore, we propose a framework for socially responsible PPPs aimed at medicine development for metabolic disorders. This socially responsible PPP framework could stimulate successful and accessible medicine development for IEMs as well as other rare diseases if the establishment of such collaborations includes terms securing joint data ownership and evidence generation, fast access, and socially responsible pricing.

Prioritization and functional validation of target genes from single-cell transcriptomics studies

Translation of academic results into clinical practice is a formidable unmet medical need. Single-cell RNA-sequencing (scRNA-seq) studies generate long descriptive ranks of markers with predicted biological function, but without functional validation, it remains challenging to know which markers truly exert the putative function. Given the lengthy/costly nature of validation studies, gene prioritization is required to select candidates. We address these issues by studying tip endothelial cell (EC) marker genes because of their importance for angiogenesis. Here, by tailoring Guidelines On Target Assessment for Innovative Therapeutics, we in silico prioritize previously unreported/poorly described, high-ranking tip EC markers. Notably, functional validation reveals that four of six candidates behave as tip EC genes. We even discover a tip EC function for a gene lacking in-depth functional annotation. Thus, validating prioritized genes from scRNA-seq studies offers opportunities for identifying targets to be considered for possible translation, but not all top-ranked scRNA-seq markers exert the predicted function.

Success Factors of Startups in Research Literature within the Entrepreneurial Ecosystem

What are the most important factors for the success of a startup? This study aims to shed light on this issue through the statistical analysis of a bibliographical sample of 60 recent articles. Through a detailed study of the selected literature, but from the perspective of business experience, we have identified the comparative relevance of those factors that recent research has highlighted as the main drivers of start-up success. Our analysis allows us to define a core of seven practical business success factors supported by the academic literature (Core-7 SF). This core makes it possible to identify the intersection between success in business practice and academic research. Our Core-7 SF shows that the most important variable to predict the success of a start-up is the Idea, followed by the CEO’s Leadership, the Business Model, the Marketing approach, and the Entrepreneurial Team. In addition, we found some differences between the geographic areas of affiliation of the authors, suggesting that cultural characteristics influence the weight given to the various reasons for success.

A novel maturity index for assessing medical device startups

Background

Startup companies in the healthcare sector often fail because they lack sufficient entrepreneurial, regulatory, and business development expertise. Maturity models provide useful frameworks to assess the state of business elements more systematically than heuristic assessments. However, previous models were developed primarily to characterize the business state of larger nonmedical companies. A maturity index designed specifically for startup companies in the medical product sector could help to identify areas in which targeted interventions could assist business development.

Methods

A novel MedTech Startup Maturity Index (SMI) was developed by a collaborative team of academic and industry experts and refined through feedback from external stakeholders. Pediatric medical device startups associated with the West Coast Consortium for Technology & Innovation in Pediatrics (CTIP) were scored and ranked according to the SMI following semi-structured interviews. The CTIP executive team independently ranked the maturity of each company based on their extensive experiences with the same companies.

Results

SMI scores for 16 companies ranged from 1.2 to 3.8 out of 4. These scores were well aligned with heuristic CTIP rankings for 14 out of 16 companies, reflected by strong correlations between the two datasets (Spearman's rho = 0.721, P = 0.002, and Kendall's tau-b = 0.526, P = 0.006).

Conclusions

The SMI yields maturity scores that correlate well with expert rankings but can be assessed without prior company knowledge and can identify specific areas of concern more systematically. Further research is required to generalize and validate the SMI as a pre-/post-evaluation tool.

Identification of β-Lactams Active against Mycobacterium tuberculosis by a Consortium of Pharmaceutical Companies and Academic Institutions

Rising antimicrobial resistance challenges our ability to combat bacterial infections. The problem is acute for tuberculosis (TB), the leading cause of death from infection before COVID-19. Here, we developed a framework for multiple pharmaceutical companies to share proprietary information and compounds with multiple laboratories in the academic and government sectors for a broad examination of the ability of β-lactams to kill Mycobacterium tuberculosis (Mtb). In the TB Drug Accelerator (TBDA), a consortium organized by the Bill & Melinda Gates Foundation, individual pharmaceutical companies collaborate with academic screening laboratories. We developed a higher order consortium within the TBDA in which four pharmaceutical companies (GlaxoSmithKline, Sanofi, MSD, and Lilly) collectively collaborated with screeners at Weill Cornell Medicine, the Infectious Disease Research Institute (IDRI), and the National Institute of Allergy and Infectious Diseases (NIAID), pharmacologists at Rutgers University, and medicinal chemists at the University of North Carolina to screen ∼8900 β-lactams, predominantly cephalosporins, and characterize active compounds. In a striking contrast to historical expectation, 18% of β-lactams screened were active against Mtb, many without a β-lactamase inhibitor. One potent cephaloporin was active in Mtb-infected mice. The steps outlined here can serve as a blueprint for multiparty, intra- and intersector collaboration in the development of anti-infective agents.

Improving Translational Paradigms in Drug Discovery and Development

Despite improved knowledge regarding disease causality, new drug targets, and enabling technologies, the attrition rate for compounds entering clinical trials has remained consistently high for several decades, with an average 90% failure rate. These failures are manifested in an inability to reproduce efficacy findings from animal models in humans and/or the occurrence of unexpected safety issues, and reflect failures in T1 translation. Similarly, an inability to sequentially demonstrate compound efficacy and safety in Phase IIa, IIb, and III clinical trials represents failures in T2 translation. Accordingly, T1 and T2 translation are colloquially termed 'valleys of death'. Since T2 translation dealt almost exclusively with clinical trials, T3 and T4 translational steps were added, with the former focused on facilitating interactions between laboratory- and population-based research and the latter on 'real world' health outcomes. Factors that potentially lead to T1/T2 compound attrition include: the absence of biomarkers to allow compound effects to be consistently tracked through development; a lack of integration/'de-siloing' of the diverse discipline-based and technical skill sets involved in drug discovery; the industrialization of drug discovery, which via volume-based goals often results in quantity being prioritized over quality; inadequate project governance and strategic oversight; and flawed decision making based on unreliable/irreproducible or incomplete data. A variety of initiatives have addressed this problem, including the NIH National Center for Advancing Translational Sciences (NCATS), which has focused on bringing an unbiased academic perspective to translation, to potentially revitalize the process. This commentary provides an overview of the basic concepts involved in translation, along with suggested changes in the conduct of biomedical research to avoid valleys of death, including the use of Translational Scoring as a tool to avoid translational attrition and the impact of the FDA Accelerated Approval Pathway in lowering the hurdle for drug approval. © 2021 Wiley Periodicals LLC.

Best Practice Guidance for Creation and Management of Innovations in Health care and Information and Communications Technologies

Governments and publics in Europe and around the world have turned to innovation in response to the manifold economic, environmental, and societal challenges we are facing. However, innovations often end up in what is popularly termed as the "valley of death" between upstream creation and downstream product development and implementation. Consequently, the benefits of innovation do not always reach the citizens. In addition, critically informed governance of innovations matter because it allows steering of innovations in response to the values and end points desired by society. With the COVID-19 pandemic, we have witnessed the rise of digital health and new information and communications technologies (ICTs). The pandemic underscored the need for innovation governance between global North and the global South. We report and discuss, in this study, the development of the innXchange innovation wheel to improve innovation creation and management, using a case study of cooperation between Europe and Africa. The innovation wheel offers best practice guidance and framework to build capacity for innovation dimensions such as partnership mobilization, evaluation, and monitoring, not to mention innovation literacy. The framework emphasizes active engagement of all key stakeholders from the very beginning, also referred to as "systematic early dialog." We propose the incorporation of systematic early dialog as the best practice guidance in global South and global North cooperation for health care and ICT innovation. The framework is a novel instrument to help overcome the current barriers in planetary health innovation management and consequently, bring breakthrough discoveries in ICTs and innovative ideas to the people.

Why do few drug delivery systems to combat neglected tropical diseases reach the market? An analysis from the technology's stages

INTRODUCTION

Many drugs used to combat schistosomiasis, Chagas disease, and leishmaniasis (SCL) have clinical limitations such as: high toxicity to the liver, kidneys and spleen; reproductive, gastrointestinal, and heart disorders; teratogenicity. In this sense, drug delivery systems (DDSs) have been described in the literature as a viable option for overcoming the limitations of these drugs. An analysis of the level of development (TRL) of patents can help in determine the steps that must be taken for promising technologies to reach the market.

AREAS COVERED

This study aimed to analyze the stage of development of DDSs for the treatment of SCL described in patents. In addition, we try to understand the main reasons why many DDSs do not reach the market. In this study, we examined DDSs for drugs indicated by WHO and treatment of SCL, by performing a search for patents.

EXPERT OPINION

In this present work we provide arguments that support the hypothesis that there is a lack of integration between academia and industry to finance and continue research, especially the development of clinical studies. We cite the translational research consortia as the potential alternative for developing DDSs to combat NTDs.

Metal Sulfide Nanoparticle Synthesis with Ionic Liquids - State of the Art and Future Perspectives

Metal sulfides are among the most promising materials for a wide variety of technologically relevant applications ranging from energy to environment and beyond. Incidentally, ionic liquids (ILs) have been among the top research subjects for the same applications and also for inorganic materials synthesis. As a result, the exploitation of the peculiar properties of ILs for metal sulfide synthesis could provide attractive new avenues for the generation of new, highly specific metal sulfides for numerous applications. This article therefore describes current developments in metal sulfide nanoparticle synthesis as exemplified by a number of highlight examples. Moreover, the article demonstrates how ILs have been used in metal sulfide synthesis and discusses the benefits of using ILs over more traditional approaches. Finally, the article demonstrates some technological challenges and how ILs could be used to further advance the production and specific property engineering of metal sulfide nanomaterials, again based on a number of selected examples.

Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model

OBJECTIVE. Deep learning applications in radiology often suffer from overfitting, limiting generalization to external centers. The objective of this study was to develop a high-quality prostate segmentation model capable of maintaining a high degree of performance across multiple independent datasets using transfer learning and data augmentation. MATERIALS AND METHODS. A retrospective cohort of 648 patients who underwent prostate MRI between February 2015 and November 2018 at a single center was used for training and validation. A deep learning approach combining 2D and 3D architecture was used for training, which incorporated transfer learning. A data augmentation strategy was used that was specific to the deformations, intensity, and alterations in image quality seen on radiology images. Five independent datasets, four of which were from outside centers, were used for testing, which was conducted with and without fine-tuning of the original model. The Dice similarity coefficient was used to evaluate model performance. RESULTS. When prostate segmentation models utilizing transfer learning were applied to the internal validation cohort, the mean Dice similarity coefficient was 93.1 for whole prostate and 89.0 for transition zone segmentations. When the models were applied to multiple test set cohorts, the improvement in performance achieved using data augmentation alone was 2.2% for the whole prostate models and 3.0% for the transition zone segmentation models. However, the best test-set results were obtained with models fine-tuned on test center data with mean Dice similarity coefficients of 91.5 for whole prostate segmentation and 89.7 for transition zone segmentation. CONCLUSION. Transfer learning allowed for the development of a high-performing prostate segmentation model, and data augmentation and fine-tuning approaches improved performance of a prostate segmentation model when applied to datasets from external centers.

Precision health: A pragmatic approach to understanding and addressing key factors in autoimmune diseases

The past decade has witnessed a significant paradigm shift in the clinical approach to autoimmune diseases, lead primarily by initiatives in precision medicine, precision health and precision public health initiatives. An understanding and pragmatic implementation of these approaches require an understanding of the drivers, gaps and limitations of precision medicine. Gaining the trust of the public and patients is paramount but understanding that technologies such as artificial intelligences and machine learning still require context that can only be provided by human input or what is called augmented machine learning. The role of genomics, the microbiome and proteomics, such as autoantibody testing, requires continuing refinement through research and pragmatic approaches to their use in applied precision medicine.

The Medicinal Chemistry in the Era of Machines and Automation: Recent Advances in Continuous Flow Technology

Medicinal chemistry plays a fundamental and underlying role in chemical biology, pharmacology, and medicine to discover safe and efficacious drugs. Small molecule medicinal chemistry relies on iterative learning cycles composed of compound design, synthesis, testing, and data analysis to provide new chemical probes and lead compounds for novel and druggable targets. Using traditional approaches, the time from hypothesis to obtaining the results can be protracted, thus limiting the number of compounds that can be advanced into clinical studies. This challenge can be tackled with the recourse of enabling technologies that are showing great potential in improving the drug discovery process. In this Perspective, we highlight recent developments toward innovative medicinal chemistry strategies based on continuous flow systems coupled with automation and bioassays. After a discussion of the aims and concepts, we describe equipment and representative examples of automated flow systems and end-to-end prototypes realized to expedite medicinal chemistry discovery cycles.

Comparing biologicals and small molecule drug therapies for chronic respiratory diseases: An EAACI Taskforce on Immunopharmacology position paper

Chronic airway diseases such as asthma and chronic obstructive pulmonary disease (COPD), together with their comorbidities, bear a significant burden on public health. Increased appreciation of molecular networks underlying inflammatory airway disease needs to be translated into new therapies for distinct phenotypes not controlled by current treatment regimens. On the other hand, development of new safe and effective therapies for such respiratory diseases is an arduous and expensive process. Antibody-based (biological) therapies are successful in treating certain respiratory conditions not controlled by standard therapies such as severe allergic and refractory eosinophilic severe asthma, while in other inflammatory respiratory diseases, such as COPD, biologicals are having a more limited impact. Small molecule drug (SMD)-based therapies represent an active field in pharmaceutical research and development. SMDs expand biologicals' therapeutic targets by reaching the intracellular compartment by delivery as either an oral or topically based formulation, offering both convenience and lower costs. Aim of this review was to compare and contrast the distinct pharmacological properties and clinical applications of SMDs- and antibody-based treatment strategies, their limitations and challenges, in order to highlight how they should be integrated for their optimal utilization and to fill the critical gaps in current treatment for these chronic inflammatory respiratory diseases.

The price of progress: Funding and financing Alzheimer's disease drug development

INTRODUCTION

Advancing research and treatment for Alzheimer's disease (AD) and the search for effective treatments depend on a complex financial ecosystem involving federal, state, industry, advocacy, venture capital, and philanthropy funding approaches.

METHODS

We conducted an expert review of the literature pertaining to funding and financing of translational research and drug development for AD.

RESULTS

The federal government is the largest public funder of research in AD. The National Institute on Aging, National Institute of Mental Health, National Institute of General Medical Sciences, and National Center for Advancing Translational Science all fund aspects of research in AD drug development. Non-National Institutes of Health federal funding comes from the National Science Foundation, Veterans Administration, Food and Drug Administration, and the Center for Medicare and Medicaid Services. Academic Medical Centers host much of the federally funded basic science research and are increasingly involved in drug development. Funding of the "Valley of Death" involves philanthropy and federal funding through small business programs and private equity from seed capital, angel investors, and venture capital companies. Advocacy groups fund both basic science and clinical trials. The Alzheimer Association is the advocacy organization with the largest research support portfolio relevant to AD drug development. Pharmaceutical companies are the largest supporters of biomedical research worldwide; companies are most interested in late stage de-risked drugs. Drugs progressing into phase II and III are candidates for pharmaceutical industry support through licensing, mergers and acquisitions, and co-development collaborations.

DISCUSSION

Together, the funding and financing entities involved in supporting AD drug development comprise a complex, interactive, dynamic financial ecosystem. Funding source interaction is largely unstructured and available funding is insufficient to meet all demands for new therapies. Novel approaches to funding such as mega-funds have been proposed and more integration of component parts would assist in accelerating drug development.

The Need for Treatment Responsive Translational Biomarkers in Alcoholism Research

Over the past two decades, major advances have been made in the basic neuroscience of alcohol addiction. However, few of these have been translated into clinically useful treatments, which remain limited. In the past decade, psychiatric drug development in general has been stalled, with many preclinically validated mechanisms failing in clinical development. Despite the existence of appealing preclinical models in the area of addictive disorders, drug development for these conditions has been impacted by the exodus of major pharma from psychiatric neuroscience. Here, we discuss translational biomarker strategies that may help turn this tide. Following an approach patterned on an endophenotype approach to complex behavioral traits, we hypothesize that relatively simple biological measures should be sought that can be obtained both in experimental animals and in humans, and that may be responsive to alcoholism medications. These biomarkers have to be tailored to the specific mechanism targeted by candidate medications and may in fact also help identify biologically more homogeneous subpopulations of patients. We introduce as examples alcohol-induced dopamine (DA) release, measures of central glutamate levels, and network connectivity, and discuss our experience to date with these biomarker strategies.

Parallel universes of Black Six biology

Creation of lethal and synthetic lethal mutations in an experimental organism is a cornerstone of genetic dissection of gene function, and is related to the concept of an essential gene. Common inbred mouse strains carry background mutations, which can act as genetic modifiers, interfering with the assignment of gene essentiality. The inbred strain C57BL/6J, commonly known as "Black Six", stands out, as it carries a spontaneous homozygous deletion in the nicotinamide nucleotide transhydrogenase (Nnt) gene [GenBank: AH009385.2], resulting in impairment of steroidogenic mitochondria of the adrenal gland, and a multitude of indirect modifier effects, coming from alteration of glucocorticoid-regulated processes. Over time, the popular strain has been used, by means of gene targeting technology, to assign "essential" and "redundant" qualifiers to numerous genes, thus creating an internally consistent "parallel universe" of knowledge. It is unrealistic to suggest phasing-out of this strain, given the scope of shared resources built around it, however, continuing on the road of "strain-unawareness" will result in profound waste of effort, particularly where translational research is concerned. The review analyzes the historical roots of this phenomenon and proposes that building of "parallel universes" should be urgently made visible to a critical reader by obligatory use of unambiguous and persistent tags in publications and databases, such as hypertext links, pointing to a vendor's strain description web page, or to a digital object identifier (d.o.i.) of the original publication, so that any research done exclusively in C57BL/6J, could be easily identified.

REVIEWERS

This article was reviewed by Dr. Neil Smalheiser and Dr. Miguel Andrade-Navarro.

DNA microarray-based gene expression profiling of estrogenic chemicals

We summarize updated information about DNA microarray-based gene expression profiling by focusing on its application to estrogenic chemicals. First, estrogenic chemicals, including natural/industrial estrogens and phytoestrogens, and the methods for detection and evaluation of estrogenic chemicals were overviewed along with a comprehensive list of estrogenic chemicals of natural or industrial origin. Second, gene expression profiling of chemicals using a focused microarray containing estrogen-responsive genes is summarized. Third, silent estrogens, a new type of estrogenic chemicals characterized by their estrogenic gene expression profiles without growth stimulative or inhibitory effects, have been identified so far exclusively by DNA microarray assay. Lastly, the prospect of a microarray assay is discussed, including issues such as commercialization, future directions of applications and quality control methods.