Biopharmaceutical Industry Capability Building in India: Report from a Symposium

The biopharmaceutical industry is evolving with a shift in focus from recombinant proteins and antibodies towards more complex cell and gene therapies. To be competitive globally, biomanufacturers need to focus on aligning with global standards with regard to drug quality, reducing manufacturing failures and delivering drugs to market quickly. Building these capabilities requires a multifaceted approach that includes improvements in operations, quality compliance, and control strategies. To address these needs, the US Pharmacopeia (USP), the Department of Biotechnology (DBT) India, and the Confederation of Indian Industry (CII) held a symposium to discuss the requirements and gaps in the biotechnology and pharmaceutical sectors in India and other developing countries. A panel of experts from academia, manufacturing, and governmental agencies identified several drivers needed for capability building, including a skilled workforce, public–private partnerships, advanced manufacturing technologies, novel biologics, and favorable policies. This article summarizes the recommendations put forward by this panel.

Genetically engineered birds; pre-CRISPR and CRISPR era

Generating biopharmaceuticals in genetically engineered bioreactors continues to reign supreme. Hence, genetically engineered birds have attracted considerable attention from the biopharmaceutical industry. Fairly recent genome engineering methods have made genome manipulation an easy and affordable task. In this review, we first provide a broad overview of the approaches and main impediments ahead of generating efficient and reliable genetically engineered birds, and various factors that affect the fate of a transgene. This section provides an essential background for the rest of the review, in which we discuss and compare different genome manipulation methods in the pre-CRISPR and CRISPR era in the field of avian genome engineering.

Beyond building predictive models: TwinOps in biomanufacturing

<div>On the wave of more and more manufacturers embracing the pervasive mission to build digital twins, also biopharmaceutical industry envisions a significant paradigm shift of digitalisation towards an intelligent factory where bioprocesses continuously learn from data to optimise and control productivity. While extensive efforts are made to build and combine the best mechanistic and data-driven models, there has not been a complete digital twin application in pharma. One of the main reasons is that production deployment becomes more complex regarding the possible impact such digital technologies could have on vaccine products and ultimately on patients. To address current technical challenges and fill regulatory gaps, this paper explores some best practices for TwinOps in biomanufacturing – from experiment to GxP validation – and discusses approaches to oversight and compliance that could work with these best practices towards building bioprocess digital twins at scale.</div>

Beyond building predictive models: TwinOps in biomanufacturing

<div>On the wave of more and more manufacturers embracing the pervasive mission to build digital twins, also biopharmaceutical industry envisions a significant paradigm shift of digitalisation towards an intelligent factory where bioprocesses continuously learn from data to optimise and control productivity. While extensive efforts are made to build and combine the best mechanistic and data-driven models, there has not been a complete digital twin application in pharma. One of the main reasons is that production deployment becomes more complex regarding the possible impact such digital technologies could have on vaccine products and ultimately on patients. To address current technical challenges and fill regulatory gaps, this paper explores some best practices for TwinOps in biomanufacturing – from experiment to GxP validation – and discusses approaches to oversight and compliance that could work with these best practices towards building bioprocess digital twins at scale.</div>

51 Flavors: Regional Resource Configurations and Foreign Multinational Market Entry in the U.S. Biopharmaceutical Industry

Creating a sustainable regional economy requires not only attracting new local ventures, but also foreign multinationals. In this regard, understanding which resources are influential in market entry decisions is crucial given that there are different resource needs between developed (DMNE) and emerging market (EMNE) multinationals. Answering calls for more neo-configurational studies in the literature, our study uses a fuzzy-set qualitative comparative analysis (fsQCA) approach to examine foreign multinational entry decisions in 51 regions of the U.S. We constructed a novel dataset comprised of 3287 foreign firms from 61 countries and territories operating in the biopharmaceutical industry. We find that there are substantial differences in the configuration of resources that attract DMNEs and EMNEs to regions. The resource configurations in our models account for over 80% of the factors influencing DMNE and EMNE market entry location decisions. Some resources played a more important role in these decisions, such as FDI stocks, cluster size, and manufacturing intensity. Our findings show that EMNEs seek out regions with a greater abundance of different resources than DMNEs. This study provides practical implications for firms entering foreign markets as well as for policy makers who want to attract these firms to bolster their regional economic development.