Intellectual Property and Innovation: Changing Perspectives in the Indian IT Industry

Indian government has undertaken significant modifications in the IP regime of the country. This will lead to a realignment of business strategies by firms in several sectors. Similarly, with liberalization and globalization, new opportunities for IP creation may emerge for Indian firms. In this context, the paper attempts to document the emerging perspectives vis-�-vis IPRs in the Indian IT industry and explore factors that are driving the change in perspectives. Large IT firms and firms in high-end niche areas are proactively seeking IP based growth strategies. While they typically seek IP protection in Western nations and not so much in India, this has led them to perceive restrictive IP regimes more positively. IP regimes in the West are more relevant for IP creating Indian IT firms today but this may change in the near future as Indian market expands. Significant IP creation by MNC subsidiaries in India is also contributing to this change in perception. Survey data show that an average IT firm in India also perceives IP protection as an important appropriability mechanism, but access to markets and relevant complementary assets continue to be more important for appropriating profits from their economic activity. A positive view of the restrictive IP regimes also gets reflected in the demands of Indian industry associations for changes in the Indian law. Broadly, these changes in perceptions seem to be linked to the evolving global production networks, changing activity profile of Indian IT firms, emerging business opportunities and changes in the competitive scenario. The understanding of Indian IT firms of the complexities of IP regimes remains rudimentary and they will need significant preparation to deal with these IP related challenges.

Rough Road to Market: Institutional Barriers to Innovations in Africa

Translating R&D and inventive efforts into a market product is characterized by significant financial skills, and the ability to overcome technical and instititonal barriers. Research into and translation of new technologies such as biotechnology products to the market requires even greater resources. This paper aims to understand the key factors that foster or hinder the complex process of translating R&D efforts into innovative products. Different pathways exist in developed countries such as firm-level efforts, the use of IPs, the spin-off of new firms that develop new products, or a mixture of these. Developing countries differ substantially in the kinds of instruments they use because of their considerably weaker institutional environment and for this reason our framework takes a systemic and institutional perspective. The paper comtributes to this issue by examining systemic institutional barriers to commercializing biotechnology in a develping context within a systems of innovation framework.research and development, biotechnology, commercialization, innovation, Africa, learning, institution building

The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line

Iowa Engineer, Volume 2013, No. 3

https://ir.uiowa.edu/iowaengineer/1042/thumbnail.jp

An Indian effort towards affordable drugs: "generic to designer drugs"

This review discusses the progress of India from being one of the largest producers of generics to its coming of age and initiating novel drug development programs such as the Open Source Drug Discovery for tuberculosis. A few groups have also begun to emerge which focus their research on rational or structure based drug design. We discuss here some of the ongoing efforts in drug discovery in India primarily in national research institutions and academia

Cloud Computing in Emerging Biotech and Pharmaceutical Companies

The purpose of this research is to determine the qualitative advantages and disadvantages of cloud computing in emerging biotech and pharmaceutical companies. From the perspective of four small biotech and pharmaceutical organizations the research investigated the positive and negative aspects of cloud computing and how it impacted the way these organizations conduct business in an increasingly complex global community. The research techniques were mixed qualitative methods that provided cross-examination and included action research, observations, interviews, surveys, and case studies. The analysis used triangulation and resulted in the discovery of patterns and themes, which provided separate interpretations and assertions of perceived benefits and obstacles. The research indicated that small biotech and pharmaceutical companies find cloud computing very attractive with some relatively minor drawbacks, which can be mitigated with adequate planning and proper implementation

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 141)

This special bibliography lists 267 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1975

Automation in pharmaceutical sector by implementation of artificial intelligence platform: a way forward

Worldwide, there are technological advances that swift automation in several aspects of the pharmaceutical industry such as pharmacovigilance, clinical research, medical affairs, and marketing. Innovative technology like artificial intelligence (AI) emphasizes the massive use of the internet for drug development, drug safety, data analytics, communication marketing, and customer engagement to achieve the goal of pharmaceuticals and patient-centric healthcare. Presently, escalating the number of individual case safety reports (ICSRs) necessitate the support of AI in the transformation of drug safety professional. AI can be transformed and evolve the clinical trial process from the conventional method alongside benefited the cutting cost, enhancing the trial quality, and alleviate trial time by almost half. Today, AI may be efficiently implemented to lower the cost of medical information requests, besides the online chatbots to communicate with health care professionals (HCPs) and consumers. There are numerous forthcoming uses of AI which need to be executed for renovation in the field of pharmaceuticals

Artificial Intelligence for Drug Discovery: Are We There Yet?

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful drug discovery requires optimizing properties related to pharmacodynamics, pharmacokinetics, and clinical outcomes. This review discusses the use of AI in the three pillars of drug discovery: diseases, targets, and therapeutic modalities, with a focus on small molecule drugs. AI technologies, such as generative chemistry, machine learning, and multi-property optimization, have enabled several compounds to enter clinical trials. The scientific community must carefully vet known information to address the reproducibility crisis. The full potential of AI in drug discovery can only be realized with sufficient ground truth and appropriate human intervention at later pipeline stages.Comment: 30 pages, 4 figures, 184 reference