Analysis of pharma R&D productivity - a new perspective needed.

R&D productivity continues to be the industry's grand challenge. We analyzed the R&D input, output, and outcome of 16 leading research-based pharmaceutical companies over 20 years (2001-2020). Our analysis shows that pharma companies increased their R&D spending at a compound annual growth rate of 6% (2001-2020) to an average R&D expenditure per company of $6.7 billion (2020). The companies in our investigation launched 251 new drugs representing 46% of all CDER-related FDA approvals in the past 20 years. The average R&D efficiency of big pharma was $6.16 billion total R&D expenditures per new drug. Almost half of the leading companies needed to compensate for their negative R&D productivity through mergers and acquisitions.

The dominant logic of Big Tech in healthcare and pharma.

Digital health and digital pharma are considered supportive tools for patients and healthcare providers (HCPs), making the market highly attractive for industry players. Not surprisingly, Tech Giants have started to move into this area. We utilized established management models and publicly available information sources, such as annual company reports, and performed a thorough analysis to uncover the underlying business models of Alphabet, Amazon, Apple, IBM, and Microsoft in order to better understand their intention and course of entering the healthcare and pharma industries. Our results indicate that Big Tech or Tech Giants do address the needs of patients and physicians, while having built clear value propositions, value chains, and revenue models to sustainably revolutionize the healthcare and pharma industries.

Open innovation: A paradigm shift in pharma R&D?

Open innovation (OI) holds promise to accelerate, diversify, and innovate research and development (R&D) in the pharmaceutical industry. It remains to be assessed in which way and to what extent OI is leveraged in practice by current pharmaceutical R&D organizations. Therefore, here we comprehensively analyzed 21 research-based pharmaceutical companies and benchmarked their implementation of OI. Our data showed that OI is an integral part of R&D of all assessed pharmaceutical companies; models typically used are research collaborations, innovation incubators, academic centers of excellence, public-private partnerships (PPPs), mergers and acquisitions (M&A), licensing, or corporate venture capital (VC) funds. In addition, we conclude that the implementation of OI differs greatly across corporations and, consequently, that R&D organizations of research-based pharmaceutical companies can be classified based on their level of OI implementation into three distinct types: predominantly traditional R&D; network-based R&D; and R&D ecosystems.

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.

R&D efficiency of leading pharmaceutical companies - A 20-year analysis.

Comparative analysis of the R&D efficiency of 14 leading pharmaceutical companies for the years 1999-2018 shows that there is a close positive correlation between R&D spending and the two investigated R&D output parameters, approved NMEs and the cumulative impact factor of their publications. In other words, higher R&D investments (input) were associated with higher R&D output. Second, our analyses indicate that there are 'economies of scale' (size) in pharmaceutical R&D.

Big Techs and startups in pharmaceutical R&D - A 2020 perspective on artificial intelligence.

We investigated what kind of artificial intelligence (AI) technologies are utilized in pharmaceutical research and development (R&D) and which sources of AI-related competencies can be leveraged by pharmaceutical companies. First, we found that machine learning (ML) is the dominating AI technology currently used in pharmaceutical R&D. Second, both Big Techs and AI startups are competent knowledge bases for AI applications. Big Techs have long-lasting experience in the digital field and offer more general IT solutions to support pharmaceutical companies in cloud computing, health monitoring, diagnostics or clinical trial management, whereas startups can provide more specific AI services to address special issues in the drug-discovery space.

The upside of being a digital pharma player.

We investigated the state of artificial intelligence (AI) in pharmaceutical research and development (R&D) and outline here a risk and reward perspective regarding digital R&D. Given the novelty of the research area, a combined qualitative and quantitative research method was chosen, including the analysis of annual company reports, investor relations information, patent applications, and scientific publications of 21 pharmaceutical companies for the years 2014 to 2019. As a result, we can confirm that the industry is in an 'early mature' phase of using AI in R&D. Furthermore, we can demonstrate that, despite the efforts that need to be managed, recent developments in the industry indicate that it is worthwhile to invest to become a 'digital pharma player'.

Open innovation and external sources of innovation. An opportunity to fuel the R&D pipeline and enhance decision making?

Historically, research and development (R&D) in the pharmaceutical sector has predominantly been an in-house activity. To enable investments for game changing late-stage assets and to enable better and less costly go/no-go decisions, most companies have employed a fail early paradigm through the implementation of clinical proof-of-concept organizations. To fuel their pipelines, some pioneers started to complement their internal R&D efforts through collaborations as early as the 1990s. In recent years, multiple extrinsic and intrinsic factors induced an opening for external sources of innovation and resulted in new models for open innovation, such as open sourcing, crowdsourcing, public-private partnerships, innovations centres, and the virtualization of R&D. Three factors seem to determine the breadth and depth regarding how companies approach external innovation: (1) the company's legacy, (2) the company's willingness and ability to take risks and (3) the company's need to control IP and competitors. In addition, these factors often constitute the major hurdles to effectively leveraging external opportunities and assets. Conscious and differential choices of the R&D and business models for different companies and different divisions in the same company seem to best allow a company to fully exploit the potential of both internal and external innovations.

Changing R&D models in research-based pharmaceutical companies.

New drugs serving unmet medical needs are one of the key value drivers of research-based pharmaceutical companies. The efficiency of research and development (R&D), defined as the successful approval and launch of new medicines (output) in the rate of the monetary investments required for R&D (input), has declined since decades. We aimed to identify, analyze and describe the factors that impact the R&D efficiency. Based on publicly available information, we reviewed the R&D models of major research-based pharmaceutical companies and analyzed the key challenges and success factors of a sustainable R&D output. We calculated that the R&D efficiencies of major research-based pharmaceutical companies were in the range of USD 3.2-32.3 billion (2006-2014). As these numbers challenge the model of an innovation-driven pharmaceutical industry, we analyzed the concepts that companies are following to increase their R&D efficiencies: (A) Activities to reduce portfolio and project risk, (B) activities to reduce R&D costs, and (C) activities to increase the innovation potential. While category A comprises measures such as portfolio management and licensing, measures grouped in category B are outsourcing and risk-sharing in late-stage development. Companies made diverse steps to increase their innovation potential and open innovation, exemplified by open source, innovation centers, or crowdsourcing, plays a key role in doing so. In conclusion, research-based pharmaceutical companies need to be aware of the key factors, which impact the rate of innovation, R&D cost and probability of success. Depending on their company strategy and their R&D set-up they can opt for one of the following open innovators: knowledge creator, knowledge integrator or knowledge leverager.

Technologically Reflective Individuals as Enablers of Social Innovation.

This paper identifies technologically reflective individuals and demonstrates their ability to develop innovations that benefit society. Technological reflectiveness (TR) is the tendency to think about the societal impact of an innovation, and those who display this capability in public are individuals who participate in online idea competitions focused on technical solutions for social problems (such as General Electric's eco-challenge, the James Dyson Award, and the BOSCH Technology Horizon Award). However, technologically reflective individuals also reflect in private settings (e.g., when reading news updates), thus requiring a scale to identify them. This paper describes the systematic development of an easy-to-administer multi-item scale to measure an individual's level of TR. Applying the TR scale in an empirical study on a health monitoring system confirmed that individuals' degree of TR relates positively to their ability to generate (1) more new product features and uses, (2) features with higher levels of societal impact, and (3) features that are more elaborated. This scale allows firms seeking to implement co-creation in their new product development (NPD) process and sustainable solutions to identify such individuals. Thus, this paper indicates that companies wishing to introduce new technological products with a positive societal impact may profit from involving technologically reflective individuals in the NPD process.

Models for open innovation in the pharmaceutical industry.

The nature of the pharmaceutical industry is such that the main driver for its growth is innovation. In view of the vast challenges that the industry has been facing for several years and, in particular, how to manage stagnating research and development (R&D) productivity, pharmaceutical companies have opened their R&D organizations to external innovation. Here, we identify and characterize four new types of open innovator, which we call 'knowledge creator', 'knowledge integrator', 'knowledge translator' and 'knowledge leverager', and which describe current open R&D models.

Getting the most out of your IP--patent management along its life cycle.

Effectively managing and optimizing the value of the patent portfolio is a major challenge for many firms, especially those in knowledge intensive industries, such as the pharmaceutical, biotechnological and chemical industry. However, insights on effective patent portfolio strategies are rare. Therefore, in this article we investigate in detail how firms successfully manage and optimize their patent portfolios to increase their overall competitiveness. We discover that successful patent portfolio management is rooted in managing the patents along their life cycles. Based on the findings of ten case studies, we develop a holistic patent life cycle management model reflecting five distinctive phases of patent management: explore, generate, protect, optimize and decline. We conclude with how our findings can be used in practice.

Pannexin1 and Pannexin2 channels show quaternary similarities to connexons and different oligomerization numbers from each other.

Pannexins are homologous to innexins, the invertebrate gap junction family. However, mammalian pannexin1 does not form canonical gap junctions, instead forming hexameric oligomers in single plasma membranes and intracellularly. Pannexin1 acts as an ATP release channel, whereas less is known about the function of Pannexin2. We purified cellular membranes isolated from MDCK cells stably expressing rat Pannexin1 or Pannexin2 and identified pannexin channels (pannexons) in single membranes by negative stain and immunogold labeling. Protein gel and Western blot analysis confirmed Pannexin1 (Panx1) or Pannexin2 (Panx2) as the channel-forming proteins. We expressed and purified Panx1 and Panx2 using a baculovirus Sf9 expression system and obtained doughnut-like structures similar to those seen previously in purified connexin hemichannels (connexons) and mammalian membranes. Purified pannexons were comparable in size and overall appearance to Connexin46 and Connexin50 connexons. Pannexons and connexons were further analyzed by single-particle averaging for oligomer and pore diameters. The oligomer diameter increased with increasing monomer molecular mass, and we found that the measured oligomeric pore diameter for Panxs was larger than for Connexin26. Panx1 and Panx2 formed active homomeric channels in Xenopus oocytes and in vitro vesicle assays. Cross-linking and native gels of purified homomeric full-length and a C-terminal Panx2 truncation mutant showed a banding pattern more consistent with an octamer. We purified Panx1/Panx2 heteromeric channels and found that they were unstable over time, possibly because Panx1 and Panx2 homomeric pannexons have different monomer sizes and oligomeric symmetry from each other.

The M34A mutant of Connexin26 reveals active conductance states in pore-suspending membranes.

Connexin26 (Cx26) is a member of the connexin family, the building blocks for gap junction intercellular channels. These dodecameric assemblies are involved in gap junction-mediated cell-cell communication allowing the passage of ions and small molecules between two neighboring cells. Mutations in Cx26 lead to the disruption of gap junction-mediated intercellular communication with consequences such as hearing loss and skin disorders. We show here that a mutant of Cx26, M34A, forms an active hemichannel in lipid bilayer experiments. A comparison with the Cx26 wild-type is presented. Two different techniques using micro/nano-structured substrates for the formation of pore-suspending lipid membranes are used. We reconstituted the Cx26 wild-type and Cx26M34A into artificial lipid bilayers and observed single channel activity for each technique, with conductance levels of around 35, 70 and 165 pS for the wild-type. The conductance levels of Cx26M34A were found at around 45 and 70 pS.