Evolving models of collaborative drug discovery: managing intellectual capital assets

Figures & data

Table 1. Understanding the drivers, expanding models of collaboration and knowledge-based outcomes.

Drivers for open innovation	Expanding models of collaboration	Knowledge-based outcomes
Stimulating discovery; Idea generation	Prediscovery consortia	Large scale data generation and management
New market or product area entry including across convergence domains	R&D networks	Bridging the knowledge gap between pharmaceuticals, diagnostics, information technology and other technologies
Development of new core competencies	Centers of excellence	Focus on key value chain activities and human capital development
Freedom to operate through openness	Public-private partnerships	Pooling and openness of upstream information for downstream development
Knowledge sharing and access to broad skill sets	Crowd-sourcing	Knowledge sharing and access to upstream and downstream stakeholders
Globally linking innovation partners	Web-based collaborations	Market specific knowledge generation and application

Table 2. Assessing partnerships: length of partnership, accessibility and complexity.

Partnership type	One to one	One to many	Many to many
Open/Short-term (See Figure 1)	Merck-GOBDA	Bayer Grants4 Targets	Pistoia Alliance
Open/Long-term	JLABS	Parker Institute for Cancer Immunotherapy	Open Source Drug Discovery (OSDD)
Closed/Short-term	Amgen-Boston Children’s Hospital	SpringFire Laboratory Network	Accelrys Consortia
Closed/Long-term	Paraxel-Sanofi	Novartis Institutes for BioMedical Research (NIBR)	Bayer-MIT-Harvard Alliance

Figure 1. Supporting figure for Table 2.