Decoding drug search under public funding: rates, directions, and social impacts in an agent-based model

By extending the framework presented by Dosi et al. (2023b), we build an evolutionary agent-based model of the pharmaceutical sector featuring a government and a Public Research Lab investing in R&D and innovating across different therapeutic areas. After having empirically validated our baseline scenario, we experiment with different configurations of the industry embedding varying degrees of public involvement in innovative activities, participation in the collection of rewards of innovation and demand management. Simulation exercises show that the very existence of the Public Research Lab is capable of considerably moving forward the knowledge base and the related technological opportunities. Moreover, while mixed innovation systems do not significantly improve the public and private performance of the economy, more public-oriented innovation systems (Dosi and Stiglitz, 2014) increase societal welfare by spurring innovation and containing prices, and, even more important, by directing innovative search into domains of social priority.