Drug research commences with the discovery phase with AI, employing in vivo and in vitro models to identify promising lead drug compounds. In-Silico or computational methods, such as databases, quantitative SAR (structure-activity relationship), homology, and molecular modeling, expedite the generation of lead compounds with heightened accuracy, reduced costs, and shorter timeframes. More than 30 companies, spanning technology vendors, established pharmaceutical firms, and emerging start-ups, actively participate in the development and application of in-silico drug discovery. The analysis also identifies the companies leading in each innovative area and assesses the potential impact and global reach of their patenting activities across diverse applications and geographical locations. Assessing "application diversity," which quantifies the number of distinct applications associated with each relevant patent, reveals companies categorized as either specialized niche innovators or diversified across multiple domains. Similarly, "geographic reach" assesses the breadth of global application by considering the number of countries where relevant patents are registered, varying from localized to global scopes.
AI-Driven Revolution: Empowering Drug Discovery Through In-Silico Methods
Tools
Typography
- Font Size
- Default
- Reading Mode