Dataset for the study of the relationships among business model innovation, open innovation, agility, and export performance

The data comes from research analyzing the effect of business model innovation on firms' export performance and, also, the role of organizational agility and open innovation as antecedents of business model innovation. The population in this study was comprised by 1518 Spanish exporting manufacturing companies, and the final valid sample included 196 companies. To collect the data, a telephone survey was conducted using a questionnaire designed based on the literature review. PLS was used to assess the reliability and validity of the measures and to test the structural model. The results showed that the measures meet the general criteria commonly accepted by the literature, which makes them suitable for conducting replication studies. Moreover, the data can be used to go further in the study of the relationships between business model innovation and export performance and to clarify the determinants of business model innovation by considering the different dimensions of that variable, to examine some group-specific effects and to test whether some characteristics of the firms in the sample may moderate the relationships between the variables mentioned above. Since business model innovation is crucial in today´s turbulent markets, a better understanding of its antecedents and its impact on firms´ export performance can help guide managers in their decisions.

The role of open innovation in addressing resource constraints in healthcare: a systematic literature review

PURPOSE

The resource crisis in healthcare can be alleviated by engaging external stakeholders and resources in healthcare delivery. The authors use value and open innovation concepts to understand what motivates the stakeholders to join the healthcare innovation ecosystem and what value such an ecosystem brings to healthcare.

DESIGN/METHODOLOGY/APPROACH

A systematic literature review following the PRISMA framework method was applied to reach the research objective. Out of a total of 509 identified articles published till 2021, 25 were selected as relevant for this review.

FINDINGS

Six categories of actors were identified, including innovation intermediaries, which were so far neglected in the healthcare innovation literature. Furthermore, patients, healthcare providers, innovation suppliers, investors and influencers were described. The authors also distinguished internal and external stakeholders. The authors show why and how open innovation projects contribute to involving external stakeholders and resources in healthcare delivery by contributing to patient autonomy, relationship building, knowledge transfer, improving collaborative mindset and culture, advancing know-how and bringing additional finances.

ORIGINALITY/VALUE

This article is the first one to systematically describe the value of open innovation in healthcare. The authors challenge the positivist approach in value presented by value-based healthcare. The authors show how openness contributes to addressing the resource crisis by involving new stakeholders and resources in the care delivery process.

Impact of environmental sustainability on open innovation in SMEs: An empirical study considering the moderating effect of gender

Sustainable development has emerged as a crucial factor enhancing the competitiveness of small and medium enterprises (SMEs) in light of societal expectations and government regulations. Within this context, innovation assumes a significant role in this challenge, particularly for smaller companies facing greater obstacles in fostering innovation. These constraints have prompted both internal and external innovation initiatives, commonly referred to as open innovation. In this article, we scrutinize the influence of environmental practices on innovation endeavors, specifically examining whether the innovation strategy and its implementation facilitate the advancement of open innovation within SMEs. Furthermore, we explore the potential moderating effect of firm owners' gender on these relationships. The research model is validated using data from 543 companies in Ecuador, employing the partial least squares (PLS) method. The findings elucidate how environmental sustainability can promote the adoption of open innovation practices, with the innovation strategy and its implementation acting as mediators in this relationship. The impact of gender only manifests in the innovation strategy pertaining to environmental sustainability. In conclusion, open innovation stemming from the pivotal role of environmental sustainability emerges as a critical driver in augmenting innovation performance across various dimensions, such as quality, growth, efficiency, process enhancement, organizational practices, employee motivation, and acquisition of new product/service skills.

Green innovation behaviour: Impact of industry 4.0 and open innovation

Developing nations have motivated contemporary manufacturing companies to embrace green innovation and focus on smart technology that is sustainable to harness the growing economy and uplift the people. Although, scientific research in this direction has been neglected, and at the same time there are challenges to the attainment while meeting the need of the people. This study aims to investigate the impact of Industry 4.0, open innovation and green innovation performance on green innovation behaviour. To this end, a theoretical model was established. A quantitative research approach was applied in which survey data were utilized to capture 247 responses from different manufacturing companies in Malaysia. The model was tested using SmartPLSver3.0 to measure the structural relationship between variables. The findings indicate that Industry 4.0 and green innovation performance positively impact green innovation behaviour, compared to open innovation which has no impact. The impact of green innovation performance is found to be stronger when compared to Industry 4.0 and open innovation. Likewise, green innovation performance exhibits a substantial mediating impact between the exogenous variables and green innovation behaviour. The policy implication and conclusions are further discussed in the last section of the study.

Evolutionary game study of crowdsourcing open innovation synergy mechanism

Open innovation crowdsourcing can help enterprises meet the challenges of a rapidly changing environment and improve their innovation performance. This study introduces network externalities as influencing factors of the crowdsourcing open innovation synergy mechanism. This study constructed the game payment matrix of the crowdsourcing open innovation synergy mechanism, and the evolutionary game method obtained the equilibrium solution of the crowdsourcing open innovation synergy mechanism. The impact of changes in the main influencing factors on the issuers' and receivers' willingness to collaborate and innovate was explored through numerical and case studies. The study shows that the higher the synergy benefit and its allocation coefficient need to be within a reasonable range for the willingness to collaborate and innovate to increase; the lower the original cost of both parties, and the higher the cost reduction coefficient under the policy support of the crowdsourcing platform, the higher the willingness to collaborate and innovate; the higher the network externality and the lower the penalty for breach of contract, the higher the desire to collaborate and innovate. The study recommends strengthening non-school education to guide innovation for all, and refining relevant policies to tailor innovation to local conditions. This study provides a new perspective and theoretical guidance for enterprises to build a crowdsourcing open innovation synergy mechanism and is a valuable reference for open innovation management.

The ethical matrix as a method for involving people living with disease and the wider public (PPI) in near-term artificial intelligence research

INTRODUCTION

The rapid pace of research in the field of Artificial Intelligence in medicine has associated risks for near-term AI. Ethical considerations of the use of AI in medicine remain a subject of much debate. Concurrently, the Involvement of People living with disease and the Public (PPI) in research is becoming mandatory in the EU and UK. The goal of this research was to elucidate the important values for our relevant stakeholders: People with MS, Radiologists, neurologists, Registered Healthcare Practitioners and Computer Scientists concerning AI in radiology and synthesize these in an ethical matrix.

METHODS

An ethical matrix workshop co-designed with a patient expert. The workshop yielded a survey which was disseminated to the professional societies of the relevant stakeholders. Quantitative data were analysed using the Pingouin 0.53 python package. Qualitative data were examined with word frequency analysis and analysed for themes with grounded theory with a patient expert.

RESULTS

184 participants were recruited, (54, 60, 17, 12, 41 respectively). There were significant (p < 0.00001) differences in age, gender and ethnicity between groups. Key themes emerging from our results were the importance fast and accurate results, explanations over model performance and the significance of maintaining personal connections and choice. These themes were used to construct the ethical matrix.

CONCLUSION

The ethical matrix is a useful tool for PPI and stakeholder engagement with particular advantages for near-term AI in the pandemic era.

IMPLICATIONS FOR PRACTICE

We have produced an ethical matrix that allows for the inclusion of stakeholder opinion in medical AI research design.

Market capitalization shock effects on open innovation models in e-commerce: golden cut q-rung orthopair fuzzy multicriteria decision-making analysis

This research paper analyzes revenue trends in e-commerce, a sector with an annual sales volume of more than 340 billion dollars. The article evaluates, despite a scarcity of data, the effects on e-commerce development of the ubiquitous lockdowns and restriction measures introduced by most countries during the pandemic period. The analysis covers monthly data from January 1996 to February 2021. The research paper analyzes relative changes in the original time series through the autocorrelation function. The objects of this analysis are Amazon and Alibaba, as they are benchmarks in the e-commerce industry. This paper tests the shock effect on the e-commerce companies Alibaba in China and Amazon in the USA, concluding that it is weaker for companies with small market capitalizations. As a result, the effect on estimated e-trade volume in the USA was approximately 35% in 2020. Another evaluation considers fuzzy decision-making methodology. For this purpose, balanced scorecard-based open financial innovation models for the e-commerce industry are weighted with multistepwise weight assessment ratio analysis based on q-rung orthopair fuzzy sets and the golden cut. Within this framework, a detailed analysis of competitors should be made. The paper proves that this situation positively affects the development of successful financial innovation models for the e-commerce industry. Therefore, it may be possible to attract greater attention from e-commerce companies for these financial innovation products.

The Relationship Between Innovation and Corporate Performance in Japanese SMEs by Two-Stage Panel Data Analysis: Focusing on the Joint Effect of ICT and R&D

The final aim of innovation is not innovation itself but enhancing profits or sales. To complete the theory of innovation, it is required to show whether innovation contributed to improvements in business performance. A further focus of this paper is on the role of ICT and R&D in the innovation process. ICT plays a vital role in absorbing information from outside the firm, while R&D is essential for assimilating obtained information with existing resources to create something novel. The focus of this paper is on the joint effect of these two factors. The estimation is based on a two-stage probit instrumental variable (IV) panel model and the authors' own survey data of 2012 and 2018. The dependent variables are innovation in the first equation and sales in the second. The results obtained show that (i) innovation enhances sales; (ii) R&D is significant for innovation; (iii) ICT is not significant for either of the equations; and (iv) the cross term of R&D and ICT is significant for innovation, implying that ICT is an enabler of innovation. These are novel results.

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

BACKGROUND

The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools.

METHODS

In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST.

RESULTS AND CONCLUSION

The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

Open innovation: the key to advancing brain health

With the exponential growth in investment attention to brain health-solutions spanning brain wellness to mental health to neurological disorders-tech giants, payers, and biotechnology companies have been making forays into this field to identify technology solutions and pharmaceutical amplifiers. So far, their investments have had mixed results. The concept of open innovation (OI) was first coined by Henry Chesbrough to describe the paradigm by which enterprises allow free flow of ideas, products, and services from the outside to the inside and vice versa in order to remain competitive, particularly in rapidly evolving fields where there is abundant, relevant knowledge outside the traditional walls of the enterprise. In this article, we advocate for further exploration and advancement of OI in brain health.

The role of negative entropy within supply chain sustainability

With the COVID-19 pandemic, supply chains are today confronted with more uncertainties than ever before. In the face of unanticipated disruptions, being resilient and sustainable has been rewarding for supply chains in terms of competitive advantage. However, literature is still far from possessing an encompassing sustainable supply chain framework (SSCF). As a contribution to the extant literature, the present study expounds a prominent concept termed negative entropy and explores its role in the SSCF. To accomplish this goal, the effect of negative entropy on supply chain sustainability is tested. Following the open systems theory and drawing from the collaboration and information management aspects of the negative entropy, co-creation, open innovation and network governance concepts which are considered to be relevant in this context are selected to be the antecedents of negative entropy. The empirical research is conducted on prominent logistics service providers and firms from various sectors with approved research and development departments in Turkey. The obtained data were subjected to covariance-based structural equation modeling analysis via Lisrel program. According to results, negative entropy is found to be a robust element in explaining supply chain sustainability. Furthermore, whereas co-creation and network governance reflected significant effects on negative entropy, surprisingly, open innovation demonstrated no substantial impact. This paper opens up a new front in sustainable supply chain management studies with a notable empirical study introducing negative entropy in the context of open systems theory.

User-centered requirements engineering to manage the fuzzy front-end of open innovation in e-health: A study on support systems for seniors' physical activity

BACKGROUND

Although e-health potentials for improving health systems in their safety, quality and efficiency has been acknowledged, a large gap between the postulated and empirically demonstrated benefits of e-health technologies has been ascertained. E-health development has classically been technology-driven, often resulting in the design of devices and applications that ignore the complexity of the real-world setting, thus leading to slow diffusion of innovations to care. Therefore, e-health innovation needs to consider the mentioned complexity already from the start. The early phases of innovation, fuzzy front-end (FFE) defined as "the period between when an opportunity is first considered and when an idea is judged ready for development" has been identified to have the highest impact on the innovation process and its outcome. The FFE has been recognized as the most difficult stage to manage in the innovation process as it involves a high degree of uncertainty. Such a phase becomes even more difficult when different sectors and organizations are involved. Therefore, effective methods for involving different organizations and user groups in the FFE of innovation are needed.

OBJECTIVE

The aim of this study was to manage the FFE of a collaborative, open innovation (OI) process, to define a software system supporting seniors' physical activity (PA) by applying a framework of methods from software requirements engineering (RE) to elicit and analyze needs and requirements of users and stakeholders, as well as the context in which the system should be used.

METHODS

Needs and requirements of three future user groups were explored through individual- and focus group interviews. Requirements were categorized and analyzed in a workshop with a multidisciplinary team: a system overview was produced by conceptual modelling using elicited functional requirements; high-level non-functional requirements were negotiated and prioritized. Scenario descriptions of system's supportive roles in different phases of a behavioral change process were developed.

RESULTS

User-centered RE methods were successfully used to define a system and a high-level requirements description was developed based on needs and requirements from three identified user groups. The system aimed to support seniors' motivation for PA and contained four complementary sub-systems. The outcome of the study was a Concept of Operations (ConOps) document that specified the high-level system requirements in a way that was understandable for stakeholders. This document was used both to identify and recruit suitable industrial partners for the following open innovation development and to facilitate communication and collaboration in the innovation process.

CONCLUSIONS

Applying software RE methods and involving user groups in the early phases of OI can contribute to the development of new concepts that meet complex real-world requirements. Different user groups can complement each other in conveying needs and requirements from which systems can be designed. Empirical studies applying and exploring different methods used to define new e-health solutions can contribute with valuable knowledge about handling innovation FFE.

Intellectual Property Rights and Access in Crisis

The importance of access to intellectual property rights (IPR) protected subject-matter in two crucial areas - public health, and educational and cultural engagement - has been extensively demonstrated during the COVID-19 pandemic. Although they involve separate legal areas, patent and copyright, the common thread linking the two is intellectual property's difficult relationship with access in the public interest. This paper examines the tensions caused by access barriers, the tools used to reduce them and their effectiveness. It is clear that the access barriers magnified by COVID-19 are not restricted to narrow or specific contexts but are widespread. They are created by, and are a feature of, our existing IPR frameworks. Open movements provide limited remedies because they are not designed to, nor can adequately address the wide range of access barriers necessary to promote the public interest. Existing legislative mechanisms designed to remove access barriers similarly fail to effectively remedy access needs. These existing options are premised on the assumption that there is a singular "public" motivated by homogenous "interests", which fails to reflect the plurality and cross-border reality of the public(s) interest(s) underpinning the welfare goals of IPR. We conclude that a systemic re-evaluation is required and call for positive and equitable legal measures protective of the public(s) interest(s) to be built within IPR frameworks that also address non-IPR barriers. The current pandemic and development of a "new normal" provides a crucial opportunity to comprehensively consider the public(s) interest(s), not just during a global health crisis, but on an ongoing basis.

Economic savings for scientific free and open source technology: A review

Both the free and open source software (FOSS) as well as the distributed digital manufacturing of free and open source hardware (FOSH) has shown particular promise among scientists for developing custom scientific tools. Early research found substantial economic savings for these technologies, but as the open source design paradigm has grown by orders of magnitude it is possible that the savings observed in the early work was isolated to special cases. Today there are examples of open source technology for science in the vast majority of disciplines and several resources dedicated specifically to publishing them. Do the tremendous economic savings observed earlier hold today? To answer that question, this study evaluates free and open source technologies in the two repositories compared to proprietary functionally-equivalent tools as a function of their use of Arduino-based electronics, RepRap-class 3-D printing, as well as the combination of the two. The results of the review find overwhelming evidence for a wide range of scientific tools, that open source technologies provide economic savings of 87% compared to equivalent or lesser proprietary tools. These economic savings increased slightly to 89% for those that used Arduino technology and even more to 92% for those that used RepRap-class 3-D printing. Combining both Arduino and 3-D printing the savings averaged 94% for free and open source tools over commercial equivalents. The results provide strong evidence for financial support of open source hardware and software development for the sciences. Given the overwhelming economic advantages of free and open source technologies, it appears financially responsible to divert funding of proprietary scientific tools and their development in favor of FOSH. Policies were outlined that provide nations with a template for strategically harvesting the opportunities provided by the free and open source paradigm.

Activating inclusive growth in railway SMEs by workplace innovation

The digital revolution is happening, transforming the way we move and produce. Success in the digital revolution means that the rail industries need to use the best available technologies focusing on people. The managerial and organizational practices adopted by railway entities have considerable significance for Railway's ability to succeed in global competition. One of the challenges for railway entities is to deliver innovative products, offering quickness and flexibility to respond to changing demands from their customers. Non-technological innovations and especially Workplace innovation, have a key role to play in the digitalization and acceleration of technological developments, therefore in the railway sector competitiveness. This draws attention to the importance of innovation climate and employees' commitment aiming at improving staff motivation and working conditions, thereby enhancing labor productivity, organizational performance, innovation capability, reactivity to market change, and consequently business competitiveness. As with any emerging opportunity, there is no established path to follow to activate inclusive growth in railway SMEs to uptake Workplace innovation. To address these issues, this paper develops and tests a research model that covers individual behavior, organizational practices, and process practices of innovation among employees, analyzing the impact of Workplace Innovation on firm performance.

Novel chemical starting points for drug discovery in leishmaniasis and Chagas disease

Visceral leishmaniasis (VL) and Chagas disease (CD) are caused by kinetoplastid parasites that affect millions of people worldwide and impart a heavy burden against human health. Due to the partial efficacy and toxicity-related limitations of the existing treatments, there is an urgent need to develop novel therapies with superior efficacy and safety profiles to successfully treat these diseases. Herein we report the application of whole-cell phenotypic assays to screen a set of 150,000 compounds against Leishmania donovani, a causative agent of VL, and Trypanosoma cruzi, the causative agent of CD, with the objective of finding new starting points to develop novel drugs to effectively treat and control these diseases. The screening campaign, conducted with the purpose of global open access, identified twelve novel chemotypes with low to sub-micromolar activity against T. cruzi and/or L. donovani. We disclose these hit structures and associated activity with the goal to contribute to the drug discovery community by providing unique chemical tools to probe kinetoplastid biology and as hit-to-lead candidates for drug discovery.

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An open source drug discovery screen between The Tres Cantos Open Lab Foundation and Calibr at Scripps Research.

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High-throughput phenotypic screen of a 150,000-compound library against T. cruzi and L. donovani.

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Identification and characterization of 12 novel chemical series.

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7 of those 12 chemical series are active against both T. cruzi and L. donovani.

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These chemical series may be valuable tools to identify new drug targets.

Open innovation in neuroscience research and drug discovery

The pressures on the pharmaceutical industry have incentivised a number of new collaborative models of research and development which can be categorised as open innovation. Examples of the different types of models employed are discussed and some, but not all, of these have been used to promote research and drug discovery for central nervous system disorders. Some are completely open access, while others have some intellectual property restrictions. Going forward, more ways of promoting open innovation and the sharing of best practice, especially in the neurosciences, will stimulate research and hopefully accelerate new medicines development.

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.

Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis

Background: The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Results: Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Conclusions: Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics.

Academic medical centers as innovation ecosystems to address population -omics challenges in precision medicine

While the promise of the Human Genome Project provided significant insights into the structure of the human genome, the complexities of disease at the individual level have made it difficult to utilize -omic information in clinical decision making. Some of the existing constraints have been minimized by technological advancements that have reduced the cost of sequencing to a rate far in excess of Moore's Law (a halving in cost per unit output every 18 months). The reduction in sequencing costs has made it economically feasible to create large data commons capturing the diversity of disease across populations. Until recently, these data have primarily been consumed in clinical research, but now increasingly being considered in clinical decision- making. Such advances are disrupting common diagnostic business models around which academic medical centers (AMCs) and molecular diagnostic companies have collaborated over the last decade. Proprietary biomarkers and patents on proprietary diagnostic content are no longer driving biomarker collaborations between industry and AMCs. Increasingly the scope of the data commons and biorepositories that AMCs can assemble through a nexus of academic and pharma collaborations is driving a virtuous cycle of precision medicine capabilities that make an AMC relevant and highly competitive. A rebalancing of proprietary strategies and open innovation strategies is warranted to enable institutional precision medicine asset portfolios. The scope of the AMC's clinical trial and research collaboration portfolios with industry are increasingly dependent on the currency of data, and less on patents. Intrapeneurial support of internal service offerings, clinical trials and clinical laboratory services for example, will be important new points of emphasis at the academic-industry interface. Streamlining these new models of industry collaboration for AMCs are a new area for technology transfer offices to offer partnerships and to add value beyond the traditional intellectual property offering.

Open innovation: Towards sharing of data, models and workflows

Sharing of resources across organisations to support open innovation is an old idea, but which is being taken up by the scientific community at increasing speed, concerning public sharing in particular. The ability to address new questions or provide more precise answers to old questions through merged information is among the attractive features of sharing. Increased efficiency through reuse, and increased reliability of scientific findings through enhanced transparency, are expected outcomes from sharing. In the field of pharmacometrics, efforts to publicly share data, models and workflow have recently started. Sharing of individual-level longitudinal data for modelling requires solving legal, ethical and proprietary issues similar to many other fields, but there are also pharmacometric-specific aspects regarding data formats, exchange standards, and database properties. Several organisations (CDISC, C-Path, IMI, ISoP) are working to solve these issues and propose standards. There are also a number of initiatives aimed at collecting disease-specific databases - Alzheimer's Disease (ADNI, CAMD), malaria (WWARN), oncology (PDS), Parkinson's Disease (PPMI), tuberculosis (CPTR, TB-PACTS, ReSeqTB) - suitable for drug-disease modelling. Organized sharing of pharmacometric executable model code and associated information has in the past been sparse, but a model repository (DDMoRe Model Repository) intended for the purpose has recently been launched. In addition several other services can facilitate model sharing more generally. Pharmacometric workflows have matured over the last decades and initiatives to more fully capture those applied to analyses are ongoing. In order to maximize both the impact of pharmacometrics and the knowledge extracted from clinical data, the scientific community needs to take ownership of and create opportunities for open innovation.

Opening the door to innovation

Open innovation is the new buzz, with initiatives popping up left and right. Here, we give a personal perspective on a very successful, knowledge-driven innovation initiated in an academia- industry alliance, which culminated in technology platforms that enable the generation of therapeutic antibodies with novel properties. To start, we provide a general background on open innovation in the drug development field.

Framing the structure of global open innovation research

This study proposes a way of mapping open innovation research structure by quantitatively analyzing open innovation research papers retrieved from Web of Science database. A total of 130 papers are retrieved in this study and 62 papers which contain keywords are chosen for research structure visualization. Open innovation research networks are quantitatively investigated by combining network theory and keyword co-occurrence. Contour maps of open innovation are also created on the basis of networks for visualization. The networks and contour maps can be expressed differently by choosing different information as the main actors, such as the paper author, the institute, the country or the author-keywords, to reflect open innovation research structures in micro, meso, and macro-levels, respectively. The quantitative ways of exploring open innovation research structure are investigated to unveil important or emerging open innovation components as well as to demonstrate visualization of the structure of global open innovation research. The quantitative method provided in this project shows a possible way of visualizing and evaluating research community structure and thus a computerized calculation is possible for potential quantitative applications on open innovation research management, e.g. R&D resource allocation, research performance evaluation, and science map.