The integration of AI in pharma manufacturing could not only accelerate the development of lifesaving medications but also enhance the reliability and efficiency of the production pipeline, ultimately contributing to improved health care outcomes for patients.
For drug discovery, AI algorithms could analyze vast datasets to expedite the identification of potential drug candidates, predict their efficacy, and optimize formulations. In manufacturing processes, AI is can be employed for real-time monitoring and control, ensuring precise and consistent production while minimizing errors. Additionally, AI-driven robotics streamline tasks such as packaging and labeling, enhancing overall operational speed and accuracy.
While the full benefits of AI in pharma are still unfolding, companies are cautiously exploring its potential. Recognizing the need for expertise, many pharma manufacturers are strategically collaborating with tech-savvy companies. These partnerships serve as a collaborative bridge, allowing the industry to navigate the uncharted territory of AI while leveraging external proficiency to unlock its potential benefits.
Here’s a look at some of the pharma deals from 2023.
Deal value: $389 million
In January, German biotech BioNTech acquired AI startup InstaDeep for an initial payment of ~$389 million, with shareholders being eligible for additional performance-based milestone payments of up to ~$243 million.
The acquisition followed a multi-year collaboration that resulted in various AI applications, including an 'AI innovation Lab' in 2020. Projects involved using AI for neoantigen selection, ribological sequence optimization for BioNTech’s RiboCytokine and RiboMab platforms, and an Early Warning System for high-risk SARS-CoV-2 variants.
InstaDeep, founded in 2014, focuses on AI product development and collaborates with academic institutions like the University of Oxford, the University of Michigan, and MIT.
In March, Belgian pharma company UCB and causal AI company Aitia announced a collaboration focusing on early drug discovery for Huntington's disease. The partnership aims to discover and validate novel drug targets linked to clinical endpoints in Huntington's disease, leveraging Aitia's Gemini Digital Twins and UCB's expertise in neurodegeneration research.
With an estimated 1 in 10,000 people affected worldwide and no cure, the collaboration seeks to accelerate breakthrough therapies for this challenging disease.
In April, Moderna announced a collaboration with IBM to explore next-generation technologies, including quantum computing and AI, to advance and accelerate mRNA research and science.
The partnership aims to harness breakthroughs in AI and quantum computing for mRNA medicine design and includes Moderna's participation in the IBM Quantum Accelerator program, with access to quantum computing systems and expertise for exploring cutting-edge life sciences applications.
The partnership also involves the application of AI models, including MoLFormer, to optimize lipid nanoparticles and mRNA for enhanced safety and performance in disease treatment.
Deal value: $250 million
In May, XtalPi revealed a collaboration with Eli Lilly in AI drug discovery, valued at up to $250 million in upfront and milestone payments. XtalPi's integrated AI capabilities and robotics platform will be employed to de novo design and deliver drug candidates for an undisclosed target.
The collaboration builds upon XtalPi's expertise in combining AI "dry lab" algorithms with large-scale "wet lab" robotics. XtalPi's Autonomous Labs, featuring hundreds of workstations and AGVs, will collaborate closely with Lilly to employ their AI drug discovery solution in generating a novel compound for clinical and commercial development.
XtalPi's ID4Inno small-molecule drug discovery platform, fueled by AI, autonomous labs, and expert domain knowledge, can facilitate rapid lead series identification through iterative design-make-test-analyze cycles.
In June, Sanofi pledged to become the first pharma company powered by artificial intelligence, announcing that it was 'all in' and launching an AI app called plai.
Developed in collaboration with AI platform company Aily Labs, plai will deliver real-time, reactive data interactions and give Sanofi 360-degree views across all its activities. The app collects internal data from various departments and uses AI to offer timely insights and personalized 'what if' scenarios.
Deal value: $840 million
In September, Verge Genomics, a biotech company specializing in AI-driven drug discovery using patient tissue data, partnered with Alexion, AstraZeneca’s rare disease unit. The collaboration aims to identify new drug targets for rare neurodegenerative and neuromuscular diseases.
In a deal that could reach $840 million, the partnership will leverage Verge's proprietary platform, Converge, which combines human tissue datasets with machine learning to identify high-probability clinical success targets. Alexion will select targets for each condition and holds the option to advance them through development and commercialization.
Verge's unique approach, utilizing proprietary genomic datasets from human tissue, accelerates insights into clinical candidates compared to traditional models. The platform played a pivotal role in advancing Verge's lead program in amyotrophic lateral sclerosis.
In July 2023, Recursion's CTO, Ben Mabey, announced a multi-year collaboration with Nvidia, accompanied by a $50 million investment in Recursion.
The collaboration involves large model training, joint research, and product co-development, focusing on exploring the commercial possibilities of data as a value driver, and includes plans to release ML and AI models through Nvidia's BioNeMo platform.
In August, BlueRock Therapeutics partnered with bit.bio to explore the application of bit.bio's opti-ox cell programming technology for reprogramming induced pluripotent stem cells (iPSCs) into regulatory T-cells (Tregs). Tregs, essential for maintaining immune system balance and controlling immune reactions, hold promise for iPSC-derived therapies targeting autoimmune and inflammatory disorders.
Under the agreement, bit.bio will utilize its machine learning-powered discovery platform to identify transcription factor combinations for iPSC-to-Treg reprogramming. BlueRock will have the option to license bit.bio's opti-ox precision cell programming technology to regulate the expression of transcription factor combinations in Treg cell therapies.
The opti-ox approach, employing a dual genomic safe harbor strategy, facilitates transcription factor-mediated conversion of iPSCs into specific cell types in a single step, ensuring high purity and consistency at an industrial scale within days.
BlueRock will take charge of the global development and commercialization of therapeutic candidates resulting from the collaboration. Bit.bio received an upfront payment along with potential milestone payments and royalties based on global sales of therapies emerging from the partnership.
Deal value: $1.5 billion
In September, Otsuka and ShapeTX, a programmable medicine company using AI and RNA, collaborated on developing adeno-associated viruses (AAVs) for ocular diseases.
The partnership harnesses ShapeTX's AAVidTM capsid discovery platform and transgene engineering technology, alongside Otsuka's expertise in genetic payload design and ophthalmology, to create innovative treatments for serious eye diseases.
ShapeTX's AI-driven AAVid platform, combining massive screening and machine learning, identifies precise AAV capsids for targeted treatment while minimizing off-target effects.
Under the agreement, ShapeTX received an initial payment and is eligible for milestone payments exceeding $1.5 billion, along with royalties on future sales.
Deal value: $594 million
In September, BenevolentAI announced a strategic collaboration with Merck.
Merck will utilize BenevolentAI's end-to-end AI platform and tap into the expertise of interdisciplinary drug discovery scientists to identify and develop innovative compounds from Hit Identification (Hit ID) to the pre-clinical stage. BenevolentAI, with its AI chemistry design tools and wet lab facility in Cambridge (UK), will deliver small molecule drug development candidates to Merck's pipeline.
The agreement includes payments of up to $594 million, comprising an upfront payment and potential discovery, development, and commercial milestones, along with tiered royalties on net sales of commercialized products.
Deal value: $1 billion
In October 2023, Sanofi, as part of its AI-driven strategy, entered into a strategic collaboration with BioMap to co-develop AI modules for biotherapeutic drug discovery.
The collaboration will utilize California-based BioMap's AI platform, integrating large language models and super-scale computing with biotechnology to discover novel drug targets and design biologics through an enhanced understanding of proteins.
BioMap's CTO, Le Song, explained their approach, stating, "We have built a biological map of proteins using data sets from public and private sources to inform our foundational models. By utilizing automation and integrated workflows to enhance the collection of high-quality data, we can expedite the process of new hit discovery and lead optimization."
Sanofi provided an upfront payment of $10 million to BioMap, with the collaboration having the potential to exceed $1 billion.
In November, Genentech, a member of the Roche Group, entered into a generative AI collaboration for drug discovery with U.S. semiconductor giant Nvidia.
The collaboration involves utilizing the NVIDIA DGX Cloud, an AI supercomputing platform, to expedite Genentech’s drug discovery models. The primary focus is on optimizing Genentech’s drug discovery AI models within its 'lab in a loop' framework, with the overarching goal of enhancing R&D success rates. Nvidia will assist Genentech in optimizing its framework by accelerating the training and inference processes of Genentech’s drug discovery models.
Genentech plans to leverage Nvidia's BioNeMo, a platform enabling biotech companies to customize models at scale.
This collaboration marks Genentech's continued focus on AI-driven development, following its 2020 initiation of an AI-driven, multi-target drug discovery partnership with California-based Genesis Therapeutics.
Later the same month, Boehringer Ingelheim announced a collaboration with IBM, utilizing IBM's foundation model technologies for the discovery of novel candidate antibodies in the development of efficient therapeutics. The German drugmaker will access a pre-trained AI model from IBM, further fine-tuned with additional Boehringer proprietary data, aiming to realize the vision of in silico biologic drug discovery.
IBM's foundation model technologies enable the design of antibody candidates for specific targets, screened with AI-enhanced simulation to select optimal binders. Boehringer's validation step involves producing antibodies in mini-scales and experimentally assessing them. The results inform improvements to in-silico methods through feedback loops.
Deal value: $509 million
Also in November, Boehringer Ingelheim signed a licensing agreement with Phenomic AI, focusing on crucial targets in stroma-rich cancers, such as colorectal and pancreatic cancers. These cancers pose significant treatment challenges due to the protective tumor stroma that hinders therapies and supports cancer growth. Phenomic's proprietary scTx single-cell transcriptomics platform aims to identify targets to potentially overcome the barriers posed by tumor stroma.
Phenomic, based in Toronto and launched in 2020, utilizes AI/ML to reveal drug targets emerging from cell-cell interactions, focusing on novel antibody drug discovery for challenging diseases. The scTx platform integrates one of the world’s largest single-cell RNA datasets with advanced AI and machine learning algorithms for comprehensive analysis.
Under the agreement, Boehringer gains access to Phenomic's expertise in target identification and stromal biology to advance its efforts in developing first-in-class medicines for various cancers. Boehringer holds the option to license the discovered targets for novel cancer therapeutics.
Phenomic is set to receive upfront and near-term payments totaling approximately $9 million, along with the potential for over $500 million in licensing fees and milestones.
In December, Amgen announced an expanded collaboration with Amazon Web Services (AWS) to advance generative AI-based solutions for drug discovery, development and manufacturing efficiency.
Amgen and AWS are currently experimenting with generative AI and machine learning technologies, exploring applications not only in research and development but also in operational and commercial domains. Services such as Amazon Bedrock and Amazon SageMaker JumpStart are being employed for this exploration. Amgen plans to leverage AWS's global infrastructure and advanced services at a new assembly and packaging site in Ohio to establish a digital data and analytics platform powered by AWS, integrating the latest digital and robotic technology for improved operational efficiency and sustainability.
As part of the collaboration, Amgen will utilize Amazon SageMaker, a fully managed service for machine learning models. This implementation aims to reduce manual intervention, enhance safety through AI, sensors, and machine vision systems, and enable real-time prediction of equipment failures.
Deal value: $247 million
In December, AstraZeneca announced that it has partnered with generative AI specialist Absci to develop an AI-designed antibody targeting an oncology target. This collaboration aims to expedite the discovery of a potential new cancer treatment candidate by combining Absci's Integrated Drug Creation platform with AstraZeneca's oncology expertise.
Absci, based in Washington state, accelerates drug discovery by completing the data collection, AI-driven design, and wet-lab validation cycle within approximately six weeks. The company focuses on optimizing multiple drug attributes concurrently, expanding the scope of drug targets, including those previously deemed 'undruggable.'
The Financial Times reported the AstraZeneca-Absci deal at $247 million, comprising an upfront commitment, R&D funding, milestone payments, and royalties on product sales.
Deal value: $140 million
In December, Sanofi, in line with its commitment to prioritize AI, entered a multi-year research collaboration with Paris-based startup Aqemia. The partnership focuses on discovering small molecule drug candidates across various therapeutic areas, utilizing Aqemia's technology platform that integrates deep physics with scalable generative AI.
Unlike other AI platforms requiring experimental data for training, Aqemia generates this data internally through physics-based calculations at the outset of each research project.
Under the agreement, Sanofi will provide Aqemia with up to $140 million, comprising of an upfront payment and R&D milestone payments for specific therapeutic targets.