Accessing external innovation in drug discovery and development

Quantum computing's potential for drug discovery: Early stage industry dynamics

Quantum computing (QC) is expected to revolutionize drug research by performing tasks classical supercomputers are not capable of. However, practically useful quantum computation is not yet a reality, and thus it is still unclear when and whether QC will be capable of solving real-world issues in drug discovery. By identifying the QC-related activities of pharmaceutical companies, startups, and academia in the field of drug discovery and development, we show that QC has gained traction across all of these stakeholder groups, that there is focus on developing utilities related to lead optimization and compound screening, and that there is a need for collaboration in the highly dynamic QC ecosystem.

Streptococcus pneumoniae PepO promotes host anti-infection defense via autophagy in a Toll-like receptor 2/4 dependent manner

Macrophage is essential for host anti-bacterial defense by directly eliminating invading microbes and inducing a series of immune reactions. Here we identified a Streptococcus pneumoniae protein, PepO, as a TLR2/TLR4 bi-ligand. We found that PepO enhances macrophage unspecific phagocytosis and bactericidal activity, which is related to the induction of autophagy in macrophage, for the inhibition of autophagy significantly decreased the phagocytosis and bactericidal activity of PepO-treated macrophage. We confirmed that these effects of PepO are dependent on interacting with both TLR2 and TLR4. The tlr2 or tlr4 deficiency partially abolished the effect of PepO while tlr2/tlr4 deficiency abolished it completely. In vivo study demonstrated that PepO reduced the bacteria load in WT mice significantly, while the depletion of macrophage or tlr2/tlr4 deficiency abrogated the effect of PepO. Our findings suggested the therapeutic potential of PepO and provided experimental evidence for immunotherapy against infectious disease.

Can Drug Repositioning Work as a Systematical Business Model?

As a business model, drug repositioning is facing increasing challenges from both academia and industry. To examine the feasibility of drug repositioning as a systematical business model, a drug revenue formula is introduced. By breaking down key factors into indication, price, patient population, and market share, the potentiality of the drug repositioing business model is confirmed. In addition, some unworkable repositioning stratgies are also summarized.

Menagerie: A text-mining tool to support animal-human translation in neurodegeneration research

Discovery studies in animals constitute a cornerstone of biomedical research, but suffer from lack of generalizability to human populations. We propose that large-scale interrogation of these data could reveal patterns of animal use that could narrow the translational divide. We describe a text-mining approach that extracts translationally useful data from PubMed abstracts. These comprise six modules: species, model, genes, interventions/disease modifiers, overall outcome and functional outcome measures. Existing National Library of Medicine natural language processing tools (SemRep, GNormPlus and the Chemical annotator) underpin the program and are further augmented by various rules, term lists, and machine learning models. Evaluation of the program using a 98-abstract test set achieved F1 scores ranging from 0.75-0.95 across all modules, and exceeded F1 scores obtained from comparable baseline programs. Next, the program was applied to a larger 14,481 abstract data set (2008-2017). Expected and previously identified patterns of species and model use for the field were obtained. As previously noted, the majority of studies reported promising outcomes. Longitudinal patterns of intervention type or gene mentions were demonstrated, and patterns of animal model use characteristic of the Parkinson's disease field were confirmed. The primary function of the program is to overcome low external validity of animal model systems by aggregating evidence across a diversity of models that capture different aspects of a multifaceted cellular process. Some aspects of the tool are generalizable, whereas others are field-specific. In the initial version presented here, we demonstrate proof of concept within a single disease area, Parkinson's disease. However, the program can be expanded in modular fashion to support a wider range of neurodegenerative diseases.

International collaboration generates high quality clusters of pharmaceutical patents

The worldwide active patent portfolio has nearly doubled in numbers and strength since 2000. The number of active pharmaceutical patent families has tripled in the same time period. The quantitative growth results mostly from a surge of patents from China, half of them classified in A61K36 ('medicinal preparations of undetermined constitution containing material from algae, lichens, fungi or plants'). High-quality patents exhibit a slower growth curve, and cluster within the three areas biologicals; heterocyclic compounds, and cancer drugs. However, the highest concentration of high-quality patents was found when selecting patents listing inventors from at least two out of the five most important countries of origin for pharmaceutical patents: China, EP countries, Japan, South Korea and the USA.

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.

Crowdsourcing in medical research: concepts and applications

Crowdsourcing shifts medical research from a closed environment to an open collaboration between the public and researchers. We define crowdsourcing as an approach to problem solving which involves an organization having a large group attempt to solve a problem or part of a problem, then sharing solutions. Crowdsourcing allows large groups of individuals to participate in medical research through innovation challenges, hackathons, and related activities. The purpose of this literature review is to examine the definition, concepts, and applications of crowdsourcing in medicine. This multi-disciplinary review defines crowdsourcing for medicine, identifies conceptual antecedents (collective intelligence and open source models), and explores implications of the approach. Several critiques of crowdsourcing are also examined. Although several crowdsourcing definitions exist, there are two essential elements: (1) having a large group of individuals, including those with skills and those without skills, propose potential solutions; (2) sharing solutions through implementation or open access materials. The public can be a central force in contributing to formative, pre-clinical, and clinical research. A growing evidence base suggests that crowdsourcing in medicine can result in high-quality outcomes, broad community engagement, and more open science.

Leveraging Industry-Academia Collaborations in Adaptive Biomedical Innovation

Despite the rapid pace of biomedical innovation, research and development (R&D) productivity in the pharmaceutical industry has not improved broadly. Increasingly, firms need to leverage new approaches to product development and commercial execution, while maintaining adaptability to rapid changes in the marketplace and in biomedical science. Firms are also seeking ways to capture some of the talent, infrastructure, and innovation that depends on federal R&D investment. As a result, a major transition to external innovation is taking place across the industry. One example of these external innovation initiatives is the Sanofi-MIT Partnership, which provided seed funding to MIT investigators to develop novel solutions and approaches in areas of interest to Sanofi. These projects were highly collaborative, with information and materials flowing both ways. The relatively small amount of funding and short time frame of the awards built an adaptable and flexible process to advance translational science.