< PreviousM&A ROUND-UP 10 Pharma Business International www.pbiforum.net GSK - IDRx GSK, meanwhile, has entered into an agreement to snap up IDRx, a Boston- based, clinical-stage biopharmaceutical company dedicated to developing precision therapeutics for the treatment of gastrointestinal stromal tumours (GIST). GSK will pay $1bn upfront, with potential for an additional $150m success-based regulatory approval milestone payment. The deal includes lead molecule, IDRX-42, a highly selective KIT tyrosine kinase inhibitor (TKI) being developed as a first- and second-line therapy for the treatment of GIST. GSK will be responsible for success-based milestone payments as well as tiered royalties for IDRX-42 owed to Merck. GIST typically presents in the GI tract with 80% of cases driven by mutations in the KIT gene that lead to the growth, proliferation, and survival of tumour cells (primary or activating mutations). 90% of patients treated in the first-line develop new KIT mutations (secondary or resistance mutations) that typically lead to relapse with limited therapeutic options. Currently, there are no approved TKIs that inhibit the full spectrum of clinically relevant primary and secondary mutations in KIT. IDRX-42 has demonstrated activity against all key primary and secondary KIT mutations, designed to improve outcomes for patients with GIST. This breadth of mutational coverage, in addition to high selectivity which could improve tolerability, provides potential for a best- in-class profile. Luke Miels, Chief Commercial Officer, GSK, said: “IDRX-42 complements our growing portfolio in gastrointestinal cancers. This acquisition is consistent with our approach of acquiring assets that address validated targets and where there is clear unmet medical need, despite existing approved products.” Lantheus - Evergreen Theragnostics Furthermore, Lantheus, the radiopharmaceutical-focused company, has announced a definitive agreement to acquire Evergreen Theragnostics, in an all-cash transaction consisting of an upfront payment of $250m and up to $752.5m in potential milestone payments. Evergreen is a clinical-stage radiopharmaceutical firm engaged in Contract Development and Manufacturing (CDMO) services as well as drug discovery and commercialization of proprietary products. This transaction is expected to solidify Lantheus’ capabilities as a fully integrated radiopharmaceutical company. The addition of Evergreen’s scalable manufacturing capabilities and infrastructure enhances Lantheus’ ability to meet the complex demands of radiopharmaceutical development and production. The deal also expands Lantheus’ oncology diagnostic pipeline with both OCTEVY, a registrational-stage PET diagnostic agent for certain neuroendocrine tumors (NETs) that could © stock.adobe.com/yaroslav1986Pharma Business International 11 www.pbiforum.net M&A ROUND-UP complement Lantheus’ therapeutic candidate PNT2003, as well as a number of clinical and pre-clinical novel theranostic pairs. “Today marks an exciting new chapter for Evergreen as we look to join the Lantheus team,” said James Cook, CEO of Evergreen. “Lantheus’ industry expertise and financial strength will help us bring our innovations to a broad patient population faster and support our mission to improve options for cancer patients through theranostic radiopharmaceuticals. “We look forward to benefiting from Lantheus’ experience and resources to further advance our pipeline and continue developing cutting-edge therapies and diagnostics that have the potential to transform patient care. I am very pleased to have our Evergreen team join another industry-leading company with a shared vision.” Novartis - Anthos Therapeutics Finally, Novartis is swooping for Anthos Therapeutics, a privately held, clinical-stage biopharmaceutical company with abelacimab, a late-stage medicine in development for the prevention of stroke and systemic embolism in patients with atrial fibrillation. Anthos Therapeutics, launched by Blackstone Life Sciences and Novartis in 2019, has advanced abelacimab through clinical development under a license from Novartis. Abelacimab is a novel, highly selective, fully human monoclonal antibody designed to induce effective hemostasis-sparing anticoagulation through Factor XI inhibition. Phase 2 data showed a significant reduction in bleeding events in patients taking abelacimab versus a standard of care direct-oral anticoagulant in patients with atrial fibrillation (AZALEA). Three Phase 3 clinical trials are ongoing for patients at risk of arterial and venous clots, one in patients with atrial fibrillation (LILAC- TIMI 76) and two in cancer associated thrombosis (ASTER and MAGNOLIA). Under the terms of the agreement, Novartis will make an upfront payment of $925m upon closing of the transaction, subject to certain customary adjustments, and potential additional payments of up to $2.15bn upon achievement of specified regulatory and sales milestones. “We are excited to join forces to advance the development of abelacimab, a potential first-in-class treatment and safer approach for stroke prevention in atrial fibrillation as well as cancer-associated thrombosis,” said Shreeram Aradhye, M.D., President, Development and Chief Medical Officer, Novartis. “Welcoming Anthos Therapeutics strengthens our focus in the cardiovascular space and complements our portfolio of life- changing treatments, comprehensive clinical programs, and strategic collaborations that help thousands of patients with heart disease around the world.” © stock.adobe.com/Joshua A/peopleimages.comLABORATORIES 12 Pharma Business International www.pbiforum.net A rtificial intelligence in the lab industry has started to gain traction following a UK-based AI company behind the development of an AI drug discovery platform floating an additional £182 million in shares earlier this month. The company, Isomorphic Labs, also signed deals with other pharma giants worth $2.9 billion. The company, which counts Alphabet (owners of Google) as its parent company, was founded in 2021 and soon released its AI-assisted tool that is said to be capable of halving the time it takes to find new medicines by predicting how protein structures will interact with bodily and other biological systems. While AI remains controversial in many industries and is likely to be controversial in pharmaceuticals as well – at least to consumers – its usage in drug development is relatively benign. Anything an AI comes up with will be tested by humans to make sure it works without side-effects, and the AI is applying research performed by humans to make its suggestions. It is simply doing so at speeds a human cannot. The potential for AI to reduce on times involving theoretical computing like this cannot be understated, as this tool as an example has the potential to reduce drug development times by years (the average time taking as much as five years). The The future is now AI-powered drug discovery systems in labs are dominating the market. 15 ÁPharma Business International 13 www.pbiforum.net LABORATORIES © stock.adobe.com/pwmotionLABORATORIES 14 Pharma Business International www.pbiforum.net © stock.adobe.com/The Little HutPharma Business International 15 www.pbiforum.net LABORATORIES challenge may well be in convincing consumers it is safe, however. Despite the AI not being involved in synthesising or administering the drugs, and any drugs being rigorously tested, it’s likely that many consumers will feel this is a step too far, and that AI involvement cannot be trusted. Isomorphic Labs is just the latest AI company being picked up in drug development and lab work, as there has been a flurry of activity in this sector in the past few years – Exscientia (raised over $600mn), BenevolentAI (over $300mn) and Owkin (over $300mn) are three such examples in Europe alone. Some have by now been acquired by US companies, but the fast rate of development and buyouts shows how disruptive AI can be in the laboratory market, especially in drug development. Thankfully, several AI-developed drugs are even now entering or approaching the clinical trials stage of development, allowing the industry to show off their viability. So far, phase 1 success rates for drugs developed using AI have recorded a success rate of 80-90%, compared to historical industry averages of human-made drugs, which come in at around 45- 60%. However, phase 2 success rates come in at 40%, which is practically the same as it is for drugs using traditional methods. This shows there is room for improvement, but it also shows that there is no downside (found as of yet) to AI-assisted lab development. It is faster, has a higher rate of success in phase 1 trials, and on-par success in phase 2. As of yet, there’s not enough data on drugs that have made it all the way through to give a proper analysis, but the industry will be paying close attention to these novel medicines all the same. Major pharmaceutical companies are snapping up AI startups at an alarming rate because of this, and tech companies like Alphabet are doubling down on bringing new products and platforms to market to capitalise on the disruptive technology. Whether consumers like it or not, AI-assisted drug development is going to be a major factor moving forward. It will be up to pharma industries to convince people of their safety. MICROBIOLOGY AND R&D 16 Pharma Business International www.pbiforum.net The microbial question Pharma Business International 17 www.pbiforum.net MICROBIOLOGY AND R&D © stock.adobe.com/Gorodenkoff Microbiology in the lab has always been time consuming, but new advents in technology could solve some of those problems. F or many pharma companies, an important question around microbiology and microbial testing is whether to use external labs or to conduct microbial testing onsite. For smaller businesses, third party labs tend to be the more accessible option. These labs are usually associated with stringent standards and can access expertise, while being preferable during a time of labour shortages, allowing for increased productivity. With difficulties in finding people skilled in STEM subjects, relying on an external lab and, more importantly, its team of professionals, saves on having to find staff. Conversely, over time the expense of contracting outside labs has risen, whereas by bringing testing onsite, it can be completed at a lower cost. With a lower cost per test, testing can be conducted more frequently. In addition, testing can be completed quicker in- house, preventing a hold up of products until they are cleared by the results, reducing times from up to around 72 hours to an under 24-hour turnaround. Of 18 ÁMICROBIOLOGY AND R&D 18 Pharma Business International www.pbiforum.net course, investing in the equipment can involve significant expenditure, as can hiring, and training employees to collect swabs from products and surfaces. Space must also be allocated for a secure area that does not allow for cross contamination, with isolation, adequate ventilation, secure entries and more required. Moreover, to be worth the investment, it should be considered whether there will be enough testing volume. The evolution of artificial intelligence, algorithms and new bioinformatics tools and availability of data, meanwhile, is allowing the formation of novel models for predicting, preventing, and addressing outbreaks of microbes. Predictive diagnostics for instance use customised data and diagnostic tools to present real-time insights and uncover possible issues. Utilising a combination of molecular innovations and genomics applications, predictive diagnostics can help create impactful and measurable improvements to operations. Digitalisation is set to have a major impact on the R&D scene in the future, as highlighted by Deloitte who envision an interconnected ecosystem of data, platforms, instruments, and advanced analytical tools supporting scientists across teams and geographies to quickly discover breakthrough therapies. This lab is able to optimise and advance value- stream processes from target identification to preclinical development via digital innovation. To achieve this, labs need to implement a number of tools. Machine intelligence for instance is set to empower researchers, changing human-led scientific methods, and when inserted into research processes facilitates faster analysis of molecular structures and identification of promising compounds. AI in microbiology can be applied to knowledge graphs to automate target identification and validation, cutting down time spent screening molecular libraries to uncover lead molecules. AI algorithms and machine learning, which continuously learn and adapt, can guide researchers as they identify, process, and test molecules and therapies. Furthermore, AI-based computational chemistry toolkits allow scientists to delve into novel spaces and expand the pool of potential structures to consider as drug candidates, growing development pipeline size, and AI is a critical tool for efficiently and accurately reviewing data, discovering patterns, and improving analysis. The automation of lab processes is also important to smart labs - especially labs with repetitive and high-throughput processes - through physical and digital robots, taking on sample and buffer prep, pipetting, and standard analytical testing for example, with high precision, reliability, and repeatability, minimising manual work, saving time and reducing potential for human error, particularly in steps at higher risk of variability, as well as freeing up scientists to focus on activities such as result interpretation, Pharma Business International 19 www.pbiforum.net MICROBIOLOGY AND R&D decision making and creative discussions. Of course automation is present already, primarily partial automation, with just the most routine processes fully automated - those that bring the best return on investment. Looking at a fully automated lab, liquid handling systems and robotic arms can perform the assays and transfer containers between different devices, and other labs go even further, requiring no human interaction, with robotic arms taking samples from storage, transferring them to an analytical device, and the scientist checking data. Meanwhile to enhance the work of staff, digital assistants with augmented reality (AR), virtual reality (VR), natural language processing (NLP), and computer vision can enable hands-free work, presenting a lab procedure’s steps, notes from prior experiments, and record video and audio observations. © stock.adobe.com/Gorodenkoff © stock.adobe.com/eplisterraNext >