The academic-industrial complex: navigating the translational and cultural divide

Preparing healthcare, academic institutions and notified bodies for their involvement in the innovation of medical devices under the new European regulation

INTRODUCTION

Favouring innovation by making timely medical technology available to people and by securing patients' safety is a challenge.

AREAS COVERED

The new European medical device regulation (MDR) will have a central implication in the development of new devices and could affect their innovation and availability, as well as discourage investment in research within Europe.

EXPERT OPINION

Start-ups and small companies might not be able to cope with the increasing complexity and the required changes of perspective. Healthcare institutions are facing an increasing availability of complex technologies, while data on their clinical efficacy and cost-effectiveness are rarely provided.

A partnership/collaboration between healthcare institutions, academia and private industries will enhance their own specific interests with the common goal of improving overall health and quality of life. The complexity of the subject combined with the variety of specialists and stakeholders involved requires the implementation, in hospital centres of clinical excellence, of units dedicated to the whole path of the medical device innovation. Stakeholders should quickly provide adequate measures to facilitate the complex medical device innovation path under the more stringent MDR aimed to increase safety and quality of care.

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.

On the road to smart biomaterials for bone research: definitions, concepts, advances, and outlook

The demand for biomaterials that promote the repair, replacement, or restoration of hard and soft tissues continues to grow as the population ages. Traditionally, smart biomaterials have been thought as those that respond to stimuli. However, the continuous evolution of the field warrants a fresh look at the concept of smartness of biomaterials. This review presents a redefinition of the term "Smart Biomaterial" and discusses recent advances in and applications of smart biomaterials for hard tissue restoration and regeneration. To clarify the use of the term "smart biomaterials", we propose four degrees of smartness according to the level of interaction of the biomaterials with the bio-environment and the biological/cellular responses they elicit, defining these materials as inert, active, responsive, and autonomous. Then, we present an up-to-date survey of applications of smart biomaterials for hard tissues, based on the materials' responses (external and internal stimuli) and their use as immune-modulatory biomaterials. Finally, we discuss the limitations and obstacles to the translation from basic research (bench) to clinical utilization that is required for the development of clinically relevant applications of these technologies.

Investigator brochures for phase I/II trials lack information on the robustness of preclinical safety studies

AIM

Meaningful and ethical phase I/II trials can only be conducted with supportive prospective risk-benefit assessment. This relies largely on preclinical animal studies addressing the safety and efficacy of treatments. These studies are reported in an Investigator's Brochure (IB) to inform ethics review boards and regulatory authorities. Our study investigated the extent, reporting quality and accessibility of preclinical safety studies (PCSSs) compiled in IBs.

METHODS

We analysed a sample of 46 IBs for phase I/II trials approved at a leading German university medical centre from 2010 to 2016. We extracted all PCSSs presented in the 46 IBs and assessed them for reporting on methodological measures to reduce validity threats.

RESULTS

The 46 IBs included 777 PCSSs. Blinded outcome assessment, randomization and sample size calculation were reported for fewer than 1% of studies. Only 5% of the PCSSs provided a reference to published data. Compliance with Good Laboratory Practice (GLP) guidance was reported for 52% of PCSSs, but the GLP document itself does not include any relevant methodological requirements for the reduction of validity threats.

CONCLUSION

Scarce reporting in IBs and the very limited publicly available data on PCSSs make it almost impossible for investigators to critically evaluate the robustness of preclinical evidence of drug safety. Combined with recent findings on the presentation of preclinical efficacy studies in IBs, we conclude that the current reporting patterns in IBs strongly limit the independent review of evidential support for early human trials. Regulatory authorities and IRBs should require better reporting in IBs.

Academic collaborations with industry: lessons for the future

Academic centers and industry partners have had love-hate relationships for more than a century. Despite many examples of socially beneficial collaborations between academia and industry, it has become increasingly difficult to find an arrangement where neither clinicians/researchers working with industry nor industry itself is demonized. Regardless, we must incentivize innovation. Preclinical research is primarily funded by the government, whereas 70% of clinical research is supported by industry. Due to external political pressure and industry's concern about lack of control over content, industry's support of continuing medical education (CME) has shrunk to 10% from 40% and has led to diversion of funding to non-CME events. Despite scrutiny of clinical faculty members' interactions with industry, corporate philanthropy is much sought after by academic institutions. Developing new therapeutics requires both academia and industry to transparently and ethically partner with creation of innovative start-ups, sharing of non-proprietary clinical trial data, and in postmarketing surveillance. The search continues for truly symbiotic relationships between academia and industry.

Costs of Implementing Quality in Research Practice

Using standardized guidelines in preclinical research has received increased interest in light of recent concerns about transparency in data reporting and apparent variation in data quality, as evidenced by irreproducibility of results. Although the costs associated with supporting quality through a quality management system are often obvious line items in laboratory budgets, the treatment of the costs associated with quality failure is often overlooked and difficult to quantify. Thus, general estimations of quality costs can be misleading and inaccurate, effectively undervaluing costs recovered by reducing quality defects. Here, we provide examples of quality costs in preclinical research and describe how we have addressed misconceptions of quality management implementation as only marginally beneficial and/or unduly burdensome. We provide two examples of implementing a quality management system (QMS) in preclinical experimental (animal) research environments - one in Europe, the German Mouse Clinic, having established ISO 9001 and the other in the United States, the University of Kentucky (UK), having established Good Laboratory Practice-compliant infrastructure. We present a summary of benefits to having an effective QMS, as may be useful in guiding discussions with funders or administrators to promote interest and investment in a QMS, which ultimately supports shared, mutually beneficial outcomes.

The impact of external innovation on new drug approvals: A retrospective analysis

Pharmaceutical companies are relying more often on external sources of innovation to boost their discovery research productivity. However, more in-depth knowledge about how external innovation may translate to successful product launches is still required in order to better understand how to best leverage the innovation ecosystem. We analyzed the pre-approval publication histories for FDA-approved new molecular entities (NMEs) and new biologic entities (NBEs) launched by 13 top research pharma companies during the last decade (2006-2016). We found that academic institutions contributed the majority of pre-approval publications and that publication subject matter is closely aligned with the strengths of the respective innovator. We found this to also be true for candidate drugs terminated in Phase 3, but the volume of literature on these molecules is substantially less than for approved drugs. This may suggest that approved drugs are often associated with a more robust dataset provided by a large number of institutes. Collectively, the results of our analysis support the hypothesis that a collaborative research innovation environment spanning across academia, industry and government is highly conducive to successful drug approvals.

The Academic-Industrial Complexity: Failure to Launch

The pharmaceutical industry has long known that ∼80% of the results of academic laboratories cannot be reproduced when repeated in industry laboratories. Yet academic investigators are typically unaware of this problem, which severely impedes the drug development process. This academic-industrial complication is not one of deception, but rather a complex issue related to how scientific research is carried out and translated in strikingly different enterprises. This Opinion describes the reasons for inconsistencies between academic and industrial laboratories and what can be done to repair this failure of translation.

Enhancing reproducibility: Failures from Reproducibility Initiatives underline core challenges

Efforts to address reproducibility concerns in biomedical research include: initiatives to improve journal publication standards and peer review; increased attention to publishing methodological details that enable experiments to be reconstructed; guidelines on standards for study design, implementation, analysis and execution; meta-analyses of multiple studies within a field to synthesize a common conclusion and; the formation of consortia to adopt uniform protocols and internally reproduce data. Another approach to addressing reproducibility are Reproducibility Initiatives (RIs), well-intended, high-profile, systematically peer-vetted initiatives that are intended to replace the traditional process of scientific self-correction. Outcomes from the RIs reported to date have questioned the usefulness of this approach, particularly when the RI outcome differs from other independent self-correction studies that have reproduced the original finding. As a failed RI attempt is a single outcome distinct from the original study, it cannot provide any definitive conclusions necessitating additional studies that the RI approach has neither the ability nor intent of conducting making it a questionable replacement for self-correction. A failed RI attempt also has the potential to damage the reputation of the author of the original finding. Reproduction is frequently confused with replication, an issue that is more than semantic with the former denoting "similarity" and the latter an "exact copy" - an impossible outcome in research because of known and unknown technical, environmental and motivational differences between the original and reproduction studies. To date, the RI framework has negatively impacted efforts to improve reproducibility, confounding attempts to determine whether a research finding is real.