Nurturing Deep Tech to Solve Social Problems: Learning from COVID-19 mRNA Vaccine Development

mRNA and Adenoviral Vector Vaccine Platforms Utilized in COVID-19 Vaccines: Technologies, Ecosystem, and Future Directions

New technological platforms, such as mRNA and adenoviral vector vaccines, have been utilized to develop coronavirus disease 2019 (COVID-19) vaccines. These new modalities enable rapid and flexible vaccine design and cost-effective and swift manufacturing, effectively combating pandemics caused by mutating viruses. Innovation ecosystems, including universities, startups, investors, and governments are crucial for developing these cutting-edge technologies. This review summarizes the research and development trajectory of these vaccine technologies, their investments, and the support surrounding them, in addition to the technological details of each technology. In addition, this study examines the importance of an innovation ecosystem in developing novel technologies, comparing it with the case of Japan, which has lagged behind in COVID-19 vaccine development. It also explores the direction of vaccine development in the post-COVID-19 era.

Chronological Analysis of First-in-Class Drugs Approved from 2011 to 2022: Their Technological Trend and Origin

The discovery and development of first-in-class (FIC) drugs are becoming increasingly important due to increasing reimbursement pressure and personalized medication. To investigate the technological trends and origin of FIC drugs, the FIC drugs approved in the U.S. from January 2011 to December 2022 were analyzed. The analysis shows that previous major target families, viz. enzymes, G-protein coupled receptors, transporters, and transcription factors, are no longer considered major in recent years. Instead, the shares of secreted proteins/peptides and mRNAs have continuously increased from 2011-2014 to 2019-2022, suggesting that the target family of FIC drugs has shifted to molecules previously considered challenging as drug targets. Small molecules were predominant in 2011-2014, followed by a large increase in antibody medicines in 2015-2018 and further diversification of antibody medicine modalities in 2019-2022. Nucleic acid medicine has also continuously increased its share, suggesting that diversifying modalities supports the creation of FIC drugs toward challenging target molecules. Over half of FIC drugs were created by small and medium enterprises (SMEs), especially young companies established in the 1990s and 2000s. All SMEs that produced more than one FIC drug approved in 2019-2022 have the strong technological capability in a specific modality. Investment in modality technologies and facilitating mechanisms to translate academic modality technologies to start-ups might be important for enhancing FIC drug development.

Deep tech innovation for parasite diagnosis: New dimensions and opportunities

By converging advanced science, engineering, and design, deep techs are bringing a great wave of future innovations by mastering challenges and problem complexity across sectors and the field of parasitology is no exception. Remarkable research and advancements can be seen in the field of parasite detection and diagnosis through smartphone applications. Supervised and unsupervised data deep learnings are heavily exploited for the development of automated neural network models for the prediction of parasites, eggs, etc., From microscopic smears and/or sample images with more than 99% accuracy. It is expected that several models will emerge in the future wherein greater attention is being paid to improving the model's accuracy. Invariably, it will increase the chances of adoption across the commercial sectors dealing in health and related applications. However, parasitic life cycle complexity, host range, morphological forms, etc., need to be considered further while developing such models to make the deep tech innovations perfect for bedside and field applications. In this review, the recent development of deep tech innovations focusing on human parasites has been discussed focusing on the present and future dimensions, opportunities, and applications.