AI Drug Discovery BD Deal: MNCs and Biotechs Ramp Up Investments as Efficiency Gains Drive CRO Demand

Source:财联社

The STAR Market Daily, January 27thToday, Insilico Medicine announced on the Hong Kong Stock Exchange that it has reached a drug research and development strategic cooperation with Qilu Pharmaceutical Group and its subsidiary, Shanghai Qilu Pharmaceutical Research Center, and signed relevant agreements. The total amount of the agreement exceeds 931 million Hong Kong dollars, including development and sales milestone payments, as well as a single-digit percentage of subsequent net sales revenue sharing.

It is reported that the two parties will rely on Insilico Medicine's proprietary Pharma.AI solution to collaborate on the development of small molecule inhibitors for specific targets, focusing on the management of cardiovascular and metabolic diseases. According to the terms of the agreement, Insilico Medicine will utilize its self-developed Pharma.AI platform to focus on the design and optimization of novel small molecule drugs for the field of metabolic diseases, while Qilu Pharmaceutical will be responsible for subsequent development and commercialization work.

Public information shows that Insilico Medicine is a global pioneer in biotechnology, committed to integrating artificial intelligence and automation technology to accelerate drug discovery and promote innovation in the field of life sciences. Recently, the company released its self-developed cardiovascular metabolic drug portfolio at the BIO-Europe conference, covering eight candidate drugs, from lead compounds to the IND application stage, with all drug research and development processes driven by Pharma.AI.

In addition to biomedicine, the announcement shows that Insilico Medicine also plans to expand the application of Pharma.AI to advanced materials, agriculture, nutrition products, and other fields. However,So far, this company has been the most active in the AI pharmaceuticals field.On January 5, it announced an $888 million anti-tumor drug R&D agreement with Servier. According to the agreement, the former will provide Pharma.AI to screen and advance the discovery and development of anti-tumor therapies.

At present, AI-driven drug discovery has achieved numerous successes globally. Recently, several Chinese and foreign companies, including Jingtai Technology, Derui Zhikang, and Generate Biomedicines, have announced that their AI-designed drugs have entered Phase III clinical trials. Notably, Generate Biomedicines' TSLP-targeting monoclonal antibody drug GB-0895 took only four years from the initial research stage, saving nearly two years in time cost compared to similar products.

Based on this background,Tech giants, MNCs, and even Biotechs successively increase their investment in AI drug development.On January 12, NVIDIA and Eli Lilly announced a plan to jointly invest $1 billion over the next five years to establish an AI drug discovery lab; On January 20, Isomorphic Labs, the AI pharmaceutical unicorn spun off from DeepMind, announced that it would combine its AI design engine with the expertise of Janssen Pharmaceuticals, the biotech division under Johnson & Johnson, to carry out cross-modal, multi-target research collaboration.

China Postal Securities stated that, in terms of market space, the global AI-enabled drug research and development cost market size is expected to grow from USD 119 billion in 2023 to USD 746 billion by 2032, with a CAGR of 22.6%. In terms of long-term commercialization, AI+CRO/AI+Biotech remains the major trend for enterprises to generate profits: on one hand, it facilitates rapid revenue generation; on the other hand, utilizing collaborative projects can help companies iterate and upgrade their own algorithm models, building their long-term competitiveness.

In terms of investment,Guojin SecuritiesPointed out,China MedicineThe innovative strength has been unquestionable, and the continuous innovation through embracing new technologies will be the winning path for global pharmaceutical companies. Therefore, rapid investment and layout in AI-driven drug discovery and healthcare will be essential for companies in the industry.

Zheshang SecuritiesIt is emphasized that the core value of AI-driven drug discovery lies in significantly improving the efficiency of early-stage drug research. Taking Insilico Medicine's Pharma.AI as an example, it can reduce the time from target discovery to preclinical candidate confirmation from 4.5 years to 12-18 months, greatly enhancing the input-output ratio during the early research phase. The high demand for AI-driven drug discovery will lead to increased needs for validation experiments and collaborations. The substantial improvement in early-stage efficiency will quickly translate into heightened demands for preclinical, safety evaluation, and clinical CRO services. It is recommended to pay attention to traditional CRO companies that have already established strategic partnerships with AI-driven drug discovery platforms.

(Science and Technology Innovation Board Daily Report, Zhang Zhen)