European countries in the race to attract successful biopharma investment: Winners and laggers.

The post-coronavirus era will open myriad opportunities for the biopharma industry. However, the extent to which each country will take advantage of this promising new scenario will largely depend on its position in a few key areas. Here, we offer an overview of the European countries that are winning and those that are lagging behind in the race to attract the greatest investment in this industry and to attain the highest rate of successful new ventures. Our results highlight the vital importance of a sound, active funding base, especially in terms of venture capital. Our findings also suggests that general scientific foundations are not enough to secure an advantage in new venture formation.

Artificial intelligence, machine learning, and drug repurposing in cancer.

Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means.Areas covered: The authors focus on supervised ML and AI methods that make use of publicly available databases and information resources. While most of the example applications are in the field of anticancer drug therapies, the methods and resources reviewed are widely applicable also to other indications including COVID-19 treatment. A particular emphasis is placed on the use of comprehensive target activity profiles that enable a systematic repurposing process by extending the target profile of drugs to include potent off-targets with therapeutic potential for a new indication.Expert opinion: The scarcity of clinical patient data and the current focus on genetic aberrations as primary drug targets may limit the performance of anticancer drug repurposing approaches that rely solely on genomics-based information. Functional testing of cancer patient cells exposed to a large number of targeted therapies and their combinations provides an additional source of repurposing information for tissue-aware AI approaches.

The COVID-19 Innovation System.

The coronavirus disease 2019 (COVID-19) pandemic response brought forth major changes in innovation policy. This article takes stock of the key features of the COVID-19 innovation system-the network of public and private actors influencing the development and diffusion of technologies to combat the pandemic. Before the pandemic, biomedical research and development policy consisted largely of "push" funding from the public sector in support of basic research and "pull" incentives from patents to motivate private companies to invest in clinical trials and develop drugs and vaccines. In contrast, during the pandemic, public funding shifted its focus to late-stage product development and manufacturing. Procurement agreements with governments replaced traditional pull incentives from patents for the major private companies. Nonpatent barriers to competition may also have incentivized innovation. The challenges to ensuring diffusion have gained in prominence during the pandemic, though it is unclear what role patents will play in pricing and access. Some aspects of this approach to biomedical innovation may be unique to crises, but others could provide lessons for policy beyond the pandemic.

How New Models Of Vaccine Development For COVID-19 Have Helped Address An Epic Public Health Crisis.

Coronavirus disease 2019 (COVID-19) vaccine development and manufacturing have proceeded at a historically unprecedented pace. This speed may be accounted for by the unprecedented scale of resources being devoted to addressing COVID-19; an unusual intensity of cooperation, encompassing the public and private sectors and occurring both within and across national borders; and innovation with respect to both technologies (for example, new vaccine platforms) and processes (for example, vaccine clinical trials). In this article we describe and analyze how resources, cooperation, and innovation have contributed to the accelerated development of COVID-19 vaccines. Similar levels and types of public investment, models of cooperation, and harnessing of innovative processes and technologies could be applied to future epidemics and other global health challenges.

Warp-Speed Covid-19 Vaccine Development: Beneficiaries of Maturation in Biopharmaceutical Technologies and Public-Private Partnerships.

It is anticipated that effective vaccines will enable the resumption of social and economic normalcy. Current calls for masking, social distancing and other restrictive measures for the public-good are difficult to enforce and are unstainable. As ~2-4% of the 50 million SARS-CoV2-infected have succumbed to Covid-19, the US department of Health and Human Services has organized a public-private partnership called Operation Warp Speed (OWS) to develop, produce and deliver 300 million doses of safe and effective vaccines with a January 2021 target. While a majority of the 300+ Covid-19 vaccine candidates are in various stages of preclinical and early-stage clinical testing, 6 clinical candidates are supported with over 10 billion USD plus integrated resources under the OWS agenda. This unprecedented approach is investing in the manufacture of product candidates ahead of product approval. It is enabled by new gene and recombinant pharmaceutical platform technologies that are accelerating the clinical study timeline from ~10 to less than 1 year. It is anticipated that one or more of the 6 candidates under the OWS initiative will be safe, effective and provide a sustained immune response to prevent infection and disease progression. This way, social and economic activities could return to normalcy.

Drug development post COVID-19 pandemic: toward a better system to meet current and future global health challenges.

Introduction: Despite advances in drug research and development, our knowledge of the underlying molecular mechanisms of many diseases remains inadequate. This have led to limited effective medicines for several diseases. To address these challenges, efficient strategies, novel technologies, and policies are urgently needed. The main obstacles in drug discovery and development are the mounting cost, risk, and time frame needed to develop new medicines. Fair pricing and accessibility is another unmet global challenge.Areas covered: Here, the authors cover the pace, risks, cost, and challenges facing drug development processes. Additionally, they introduce disease-associated data which demand global attention and propose solutions to overcome these challenges.Expert opinion: The massive challenges encountered during drug development urgently call for a serious global rethinking of the way this process is done. A partial solution might be if many consortiums of multi-nations, academic institutions, clinicians, pharma companies, and funding agencies gather at different fronts to crowdsource resources, share knowledge and risks. Such an ecosystem can rapidly generate first-in-class molecules that are safe, effective, and affordable. We think that this article represents a wake-up call for the scientific community to immediately reassess the current drug discovery and development procedures.

A public-private partnership for the express development of antiviral leads: a perspective view.

INTRODUCTION: The COVID-19 pandemic raises the question of strategic readiness for emergent pathogens. The current case illustrates that the cost of inaction can be higher in the future. The perspective article proposes a dedicated, government-sponsored agency developing anti-viral leads against all potentially dangerous pathogen species. AREAS COVERED: The author explores the methods of computational drug screening and in-silico synthesis and proposes a specialized government-sponsored agency focusing on leads and functioning in collaboration with a network of labs, pharma, biotech firms, and academia, in order to test each lead against multiple viral species. The agency will employ artificial intelligence and machine learning tools to cut the costs further. The algorithms are expected to receive continuous feedback from the network of partners conducting the tests. EXPERT OPINION: The author proposes a bionic principle, emulating antibody response by producing a combinatorial diversity of high q uality generic antiviral leads, suitable for multiple potentially emerging species. The availability of multiple pre-tested agents and an even greater number of combinations would reduce the impact of the next outbreak. The methodologies developed in this effort are likely to find utility in the design of chronic disease therapeutics.