Pharmaceutical Technology Is Now PharmTech: A Sharper Name for a Smarter Industry

Navigating FDA Shakeups and Obesity Drug Wars

Behind the Headlines Episode 28

Ask the Expert

Outsourcing Partnerships Fuel Global Biopharma Discovery and Scale-Up

Drug Digest February 2026 

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A “Plan, Prevent, Prove” Approach

Merck Acquires Terns Pharmaceuticals | Created with Canva

On March 25, 2026, Merck, known as MSD outside the United States andCanada, announced it has entered into a definitive agreement to acquire Terns Pharmaceuticals for $53.00 per share in cash, representing an approximate equity value of $6.7 billion.

 The price reflects a premium of roughly 31% to Terns' 60-day and 42% to its 90-day volume-weighted average stock price. Both companies' boards have approved the transaction, which is expected to close in the second quarter of 2026, pending antitrust clearance and a majority tender of Terns shares.

The deal centers on TERN-701, an investigational oral drug candidate that works by binding to the ABL myristoyl pocket, a mechanism distinct from the ATP-binding site targeted by most existing therapies.

 The acquisition signals continued industry investment in allosteric inhibition as a strategy for overcoming resistance in hematologic malignancies, a challenge that has defined much of the therapeutic evolution in this space since the first BCR::ABL1 inhibitor was approved 25 years ago.

"The acquisition of Terns builds on our growing presence in hematology with TERN-701, a potential best-in-class candidate for the treatment of certain patients with chronic myeloid leukemia," said Robert M. Davis, chairman and chief executive officer, Merck, in a press release.

 "This transaction further diversifies and strengthens our position in oncology as we continue to look for opportunities to broaden our portfolio into other therapeutic areas."

What Does the Clinical Data Tell Us So Far?

TERN-701 is currently being evaluated in the Cardinal trial, a global, multi-center, Phase I/II dose escalation and expansion study enrolling patients with Philadelphia chromosome-positive chronic phase chronic myeloid leukemia who had previously received at least one tyrosine kinase inhibitor and experienced treatment failure, suboptimal response, or intolerance.

 The dose escalation portion completed in January 2025 with no dose-limiting toxicities observed up to the maximum dose of 500mg once daily.

The dose expansion phase, initiated in April 2025, randomized patients to either 320mg or 500mg once daily cohorts of up to 40 patients each.

 In January 2026, the trial was expanded further to include approximately 20 patients with specific BCR::ABL1 resistance mutations, including T315I.

Encouraging rates of major molecular response and deep molecular response were observed by week 24, including in patients with high disease burden who had received multiple prior lines of therapy, among them those previously treated with an allosteric inhibitor.

 The safety profile to date has been characterized by predominantly low-grade treatment-emergent adverse events, a low rate of severe adverse events and discontinuations, no clinically meaningful changes in blood pressure, and low rates of lipase elevation.

"Based on early clinical evidence, TERN-701, a novel allosteric BCR::ABL1 inhibitor, may have the potential to provide a meaningfully differentiated option for certain patients living with chronic myeloid leukemia," said Dean Y. Li, MD, PhD, president, Merck Research Laboratories, in a press release.

The FDA granted Orphan Drug Designation for TERN-701 for the treatment of chronic myeloid leukemia in March 2024, a regulatory milestone that carries development incentives relevant to teams planning submission timelines and manufacturing scale-up strategies.

Why Does This Acquisition Matter Beyond the Balance Sheet?

This deal reflects a broader pattern in tracking pipeline consolidation.

 Large-scale acquirers are moving earlier into clinical development, accepting Phase I/II data as a basis for multi-billion-dollar commitments when the mechanism and unmet need are sufficiently compelling. Chronic myeloid leukemia remains an area of genuine therapeutic need despite the field's progress. Resistance mutations, tolerability issues with existing agents, and the desire for faster and deeper molecular responses continue to drive demand for next-generation options.

"The first approval of a BCR::ABL1 tyrosine kinase inhibitor 25 years ago transformed the prognosis for many patients with chronic myeloid leukemia. Despite new therapeutic options, there is significant need for innovative, well-tolerated therapies with faster time to onset of molecular response leading to deeper responses and better disease control," added Li.

This transaction is expected to generate a charge of approximately $5.8 billion, or roughly $2.35 per share, recorded in both second quarter and full year 2026 results.

 Merck's existing hematology pipeline, which includes candidates in Phase III for leukemias, lymphomas, and myeloproliferative neoplasms, provides an organizational infrastructure into which TERN-701 development can be integrated.

"By working together, we will advance TERN-701, leveraging the deep expertise and significant resources at Merck, a global biopharmaceutical leader with a proven track record of delivering cancer breakthroughs for patients who need them most," said Amy Burroughs, chief executive officer, Terns, in the press release.

 "I am immensely proud of the Terns team and our work towards making a difference for people living with chronic myeloid leukemia. Finally, we extend our heartfelt thanks to the investigators, patients, and community advocates whose dedication and support make the development of TERN-701 possible."

Beyond Oncology: Merck's Long-Term Vaccine Data Adds Context to Its R&D Ambitions

The Terns acquisition arrives as Merck continues to demonstrate the long-term value of its existing portfolio.

 At the EUROGIN International Multidisciplinary HPV Congress in Vienna from March 18-21, the company presented data showing sustained effectiveness of its human papillomavirus vaccines 14 and 18 years post-vaccination, respectively, alongside findings on HPV-related oropharyngeal cancers affecting both men and women. Merck is simultaneously defending mature franchises with decades-long efficacy data while acquiring early-stage assets like TERN-701. It reflects a pipeline strategy that balances near-term revenue protection with longer-horizon oncology bets.

Merck & Co., Inc. Merck to acquire Terns Pharmaceuticals, Inc., expanding its hematology pipeline with TERN-701, a novel candidate for chronic myeloid leukemia (CML). Rahway (NJ): Merck & Co., Inc.; Mar 25, 2026. Available from: 

https://www.merck.com/news/merck-to-acquire-terns-pharmaceuticals-inc-expanding-its-hematology-pipeline-with-tern-701-a-novel-candidate-for-chronic-myeloid-leukemia-cml/

Merck & Co., Inc. Merck to present new data reinforcing long-term efficacy of GARDASIL9 and GARDASIL at the EUROGIN International Multidisciplinary HPV Congress 2026. Rahway (NJ): Merck & Co., Inc.; March 16, 2026. Available from: 

https://www.merck.com/news/merck-to-present-new-data-reinforcing-long-term-efficacy-of-gardasil9-and-gardasil-at-the-eurogin-international-multidisciplinary-hpv-congress-2026/

Articles

Merck (MSD) agreed to acquire Terns Pharmaceuticals for $53/share in cash (~$6.7B), targeting a Q2 2026 close pending antitrust clearance and tender conditions. The strategic focus is TERN-701, an oral allosteric BCR::ABL1 inhibitor binding the ABL myristoyl pocket to address resistance in chronic-phase Ph+ CML. In the Phase I/II Cardinal study, dose escalation showed no DLTs up to 500 mg QD, with early week-24 MMR/DMR signals and favorable tolerability. Orphan Drug Designation supports development. Merck also highlighted durable HPV vaccine effectiveness 14–18 years post-vaccination.

Merck acquires Terns Pharmaceuticals for $6.7B, gaining TERN-701, a promising oral CML therapy with a novel mechanism and early Phase I/II clinical data.

Merck Acquires Terns Pharmaceuticals for $6.7 Billion

Capsules with blue technology structure, 3d rendering. | Image Credit: ©Vink Fan - stock.adobe.com

Quality control processes are a pivotal aspect of pharmaceutical development and manufacturing. Good manufacturing practices developed by regulators and governments around the world provide a framework for pharmaceutical companies to work within to ensure their products are safe and effective.

 Quality control (QC) and quality assurance departments are essential to drug manufacturing, and principles like quality by design (QbD) ensure companies are meeting quality requirements.

Traditional QC activities are being expanded by artificial intelligence (AI) and other digital tools. These tools are being used by pharmaceutical companies, contract organizations, and regulators. Efforts by manufacturers to incorporate sustainable practices are also enhancing quality. And a push to move manufacturing facilities closer to home is closing the supply chain gap, making it easier to ensure quality.

How Are Digital Tools Used in Manufacturing and Supply Chain Oversight?

AI and digital tools are shifting quality oversight in the pharmaceutical industry from retrospective testing to real-time, data-driven assurance.

 This change impacts the entire life cycle of drug products, from laboratory analysis to complex global supply chains.

In laboratory settings, AI is utilized to improve the reliability and speed of QC activities. AI applications enable faster root cause analysis and real-time anomaly detection.

 Natural language processing can accelerate investigations, while “virtual witnessing” tools monitor processes to detect issues early.

 For bioanalysis, the integration of AI and machine learning has the potential to significantly improve quality, efficiency, and compliance while reducing human errors.

Regulators and standard-setting organizations are also incorporating AI tools. FDA launched its generative AI tool, Elsa, in the United States to accelerate clinical protocol reviews and scientific evaluations, helping reviewers ensure the safety and efficacy of regulated products.

 Digitalization is also streamlining the large amount of documentation required for regulatory compliance and market access. Generative AI is used to automate health technology assessment workflows, including screening thousands of literature abstracts and drafting clinical narratives. This ensures that the evidence used to justify a drug’s value is structured, transparent, and aligned across different global markets.

“It appears that regulatory authorities increasingly expect submissions to be provided in structured, machine-readable formats rather than solely as static PDF documents,” says Rory Budihandojo, an independent consultant. “Consequently, this expectation compels firms to establish robust data governance practices and to strategically plan the implementation of digitalisation initiatives to ensure that data are properly structured and aligned with the required submission formats.”

The US Pharmacopeia is developing digital reference standards and digitally structured compendial methods. These tools are designed to integrate directly into digital-first workflows, providing a foundation for consistent quality as the industry adopts more automation and AI.

Digital tools are moving quality assurance from a final checkpoint to a proactive process embedded in production, often referred to as “certification by design.”

 Real-time monitoring tools—such as process analytical technology (PAT), digital twins, and predictive models—allow manufacturers to detect and correct deviations within a validated operating space, reducing the reliance on end-product testing.

According to Budihandojo, the FDA and other regulators encourage the use of advanced technologies to monitor quality. He states that the increased use of PAT and Internet of Things devices has resulted in more effective process monitoring and control. “For example, critical process parameters can be adjusted in real time, manufacturing data can be trended and analyzed continuously, and these capabilities may support the feasibility of real-time batch review activities,” Budihandojo explains.

Digital technologies can enhance QbD efforts, says Budihandojo, “by enabling advanced data analysis and modeling approaches, such as the Taguchi method, to aid in the creation of the design of experiments. The digital technology tools allow simulation of process parameter variations and prediction of their impact on the product quality profile. Through digital modeling and simulation, manufacturers can better understand how parameter changes affect product quality and develop effective control and monitoring strategies.”

The monitoring and auditing of suppliers is essential for pharmaceutical companies and contract manufacturers to ensure the quality of the pharmaceutical supply chain.

 Digital tools can enhance these activities. Companies like AbbVie have automated contract manufacturing organization scorecards, transforming manual processes into qualified applications that refresh nightly for better transparency.

Tools used to conduct postmarket surveillance include AI-driven systems that classify and risk-rank patient complaints in seconds rather than minutes, enabling faster escalation of high-priority issues.

While these various digital tools offer significant efficiency gains in several QC activities throughout a drug’s life cycle, they do not replace human judgment. Experts remain essential for validating AI outputs and providing scientific reasoning.

 Most regulators do not yet support AI making autonomous decisions without human supervision.

Because data are at the centre of many of these systems, robust data governance and process harmonisation are required to ensure that the inputs used for AI models are valid and trustworthy.

 What is true for other processes in good manufacturing practices is true when using digital tools; work must be proven to assure regulators that quality expectations are being met. AI models must be “explainable”; if a model’s logic cannot be understood or explained, it cannot be fully trusted in a regulated environment.

Does Moving Manufacturing Closer to Home Impact Quality?

In the United States, the White House has promoted the move of drug manufacturing from countries like India and China to the US.

One of the benefits of onshoring drug manufacturing is the potential improvement of product quality by fostering a proactive and collaborative regulatory environment that allows for more rigorous oversight compared to foreign sites.

 Globalized manufacturing has historically suffered from inconsistent oversight; for example, FDA foreign inspections were significantly delayed or suspended during the COVID-19 pandemic, creating a backlog that compromised timely quality assurance.

Onshoring mitigates these geographic and political barriers, ensuring facilities remain under the continuous and pervasive oversight of domestic regulators.

A mechanism for this improvement is FDA’s PreCheck Pilot Program, which encourages early and continuous engagement between the agency and manufacturers throughout the facility development lifecycle.

 This collaboration enables FDA to provide technical advice on facility design, quality systems, and compliance issues before operations even begin, ensuring that quality standards are integrated into the infrastructure from the outset.

This quality shift is being supported by the Type V Drug Master File (DMF).

 This facility-centric repository captures detailed information regarding site layout and pharmaceutical quality system elements, allowing FDA to conduct more targeted pre-approval inspections.



Onshoring often eliminates the operational friction that often undermines quality in offshore partnerships.

 In overseas facilities, time zone lags can delay the reporting and resolution of manufacturing deviations; an issue flagged in the US may not reach an expert abroad for half a day, stretching a minor fix into a multi-day exchange.

 Domestic production also resolves language and cultural nuances regarding quality reporting.

 While US teams typically expect immediate notification and root cause analysis for any issues, some foreign teams may follow more hierarchical or delayed reporting styles, which can slow the identification of critical quality risks.

Sustainability is impacting pharmaceutical QC by building quality through sustainability by design practices, which are similar to QbD principles, as both aim to utilize scientific data to establish a “design space” that ensures product quality while minimizing environmental impact throughout the entire life cycle.

Sustainability efforts are assisting operational efficiency in quality testing, allowing companies to save money while reducing the consumption of natural resources.

 A key impact is the transition towards greener analytical procedures. For example, pharmaceutical companies and pharmacopoeias are updating standards to replace hazardous, toxic chemicals with environmentally friendly solvents in laboratory settings.

 Furthermore, there is a global initiative to modernize quality benchmarks by eliminating animal testing and adopting mature analytical procedures that significantly reduce material waste.

The industry’s move towards Pharma 5.0 involves integrating digital systems for real-time quality improvement.

 Automated systems may limit energy use and natural resource consumption by deactivating equipment when not in use.

 Real-time analysis can prevent pollution by enhancing productivity and ensuring that sustainability gains are not lost during the scale-up from development to commercial manufacturing.

Sustainability is also driving the global harmonization of regulatory standards.

 Conflicting or redundant requirements between countries can lead to an increased environmental footprint due to inefficient testing.

 By synchronizing standards, pharmacopoeias ensure that environmental progress is consistent and measurable across the value chain.

Quality systems approach to pharmaceutical current good manufacturing practice regulations. FDA. April 16, 2020. Accessed March 3, 2026. 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/quality-systems-approach-pharmaceutical-current-good-manufacturing-practice-regulations

Quality by design. EMA. Accessed March 3, 2026. 

https://www.ema.europa.eu/en/human-regulatory-overview/research-development/quality-design

FDA public meeting. Onshoring manufacturing of drugs and biological products. FDA. September 20, 2025. Accessed March 3, 2026. 

https://www.fda.gov/drugs/news-events-human-drugs/fda-public-meeting-onshoring-manufacturing-drugs-and-biological-products-09302025

Lavery P. AI and digital oversight in pharma supply chains: PDA Regulatory Conference insights. 

. September 9, 2025. Accessed March 3, 2026. 

https://www.pharmtech.com/view/ai-and-digital-oversight-in-pharma-supply-chains-pda-regulatory-conference-insights

Fagundes M. Batch certification for new manufacturing technologies: the qualified person role in a digital environment. 

. December 1, 2025. Accessed March 3, 2026. 

https://www.pharmtech.com/view/batch-certification-for-new-manufacturing-technologies-the-qualified-person-role-in-a-digital-environment

FDA expands artificial intelligence capabilities with agentic AI deployment. FDA. News release. December 1, 2025. Accessed March 3, 2026. 

https://www.fda.gov/news-events/press-announcements/fda-expands-artificial-intelligence-capabilities-agentic-ai-deployment

Dhas A. Accelerating HTA readiness with generative AI. 

. December 17, 2025. Accessed March 3, 2026. 

https://www.pharmtech.com/view/accelerating-hta-readiness-with-generative-ai

USP to lead development of digital quality standards to support adoption and regulatory confidence. USP. News release. January 22, 2026. Accessed March 3, 2026. https://www.usp.org/news/usp-leads-digital-quality-standards-development

Guidance for Industry, Quality Systems Approach to Pharmaceutical CGMP Regulations.

 US HHS. September 2006. Accessed March 3, 2026.

The White House. Regulatory relief to promote domestic production of
critical medicines. Executive Order. May 5, 2025. https://www.whitehouse.gov/presidential-actions/2025/05/regulatory-relief-to-promote-domestic-production-of-critical-medicines/

FDA launches PreCheck Pilot Program to strengthen domestic pharmaceutical manufacturing. FDA. Press release. February 1, 2026. 

https://www.fda.gov/news-events/press-announcements/fda-launches-precheck-pilot-program-strengthen-domestic-pharmaceutical-manufacturing

FDA’s support for onshoring drug manufacturing and increasing oversight of foreign facilities. Jonesday.com. Insights newsletter. December 4, 2025. 

https://www.jonesday.com/en/insights/2025/12/fdas-support-for-onshoring-drug-manufacturing-and-increasing-oversight-of-foreign-facilities

Seven forces driving onshoring in biologics manufacturing. AVID Bioservices. 

https://avidbio.com/resource/seven-forces-driving-onshoring-in-biologics-manufacturing/

FDA public meeting: onshoring manufacturing of drugs and biological products. FDA.gov. September 30, 2025. 

Schwartz MI and Kim J. Onshoring drug manufacturing: insights from FDA’s PreCheck initiative and public meeting. FDA Law Blog. October 28, 2025 

https://www.thefdalawblog.com/2025/10/onshoring-drug-manufacturing-insights-from-fdas-precheck-initiative-and-public-meeting/

Barle EL, Melton T, Judge E. Sustainability by design for pharmaceutical products. 

https://ispe.org/pharmaceutical-engineering/march-april-2023/sustainability-design-pharmaceutical-products

Haigney S, Lakavage A. The role of standards in sustainability. 

. February 3, 2026. Accessed 3 March 2026. 

https://www.pharmtech.com/view/the-role-of-standards-in-sustainability

Green chemistry: a more sustainable approach to medicine development. Pfizer. November 23, 2022. Accessed March 3, 2026. 

https://www.pfizer.com/news/articles/green_chemistry_a_more_sustainable_approach_to_medicine_development

Quality control and assurance remain central to GMP-compliant pharmaceutical manufacturing, increasingly shaped by AI-enabled and digital workflows. Advanced analytics are shifting oversight from end-product testing toward real-time, data-driven “certification by design,” supported by PAT, IoT, digital twins, and predictive modeling within validated design spaces. Regulators and standards bodies are adopting digitalization, driving expectations for structured, machine-readable submissions and robust data governance with explainable models. Onshoring can strengthen inspection continuity and collaboration, while sustainability initiatives modernize analytical methods, reduce hazardous reagents, and harmonize standards.

Quality control for pharmaceuticals is evolving with the assistance of digital tools, sustainability practices, and a push to move manufacturing onshore. 

Advancing Quality in Drug Products

In regard to their presentations at PDA Week 2026, Richard Jaenisch and David Jaenisch discuss balancing AI integration with human expertise, compliance, and IP protection.

Human-AI Training Parallelization: Empowering Life Sciences Without Replacing Expertise

In this insightful interview, Richard Jaenisch, senior director of Education, Outreach, and Digital Experience at Open BioPharma Research and Training Institute, and David Jaenisch, director of Technology at Prompting Integration and Consulting LLC (PICLLC), discuss their groundbreaking Human-AI Training Parallelization (HATP) framework, a practical approach to integrating generative AI into life sciences workflows without compromising human expertise or regulatory integrity.

At its core, HATP works by parallelizing existing systems rather than replacing them, embedding AI only where it adds value within a given workflow. The framework centers on two key methods: digitally interactive SOPs (DISOPs), which consolidate SOPs and training materials into a single transparent, auditable platform for competency-focused training; and project-based HATP (PBHATP), which captures tribal knowledge and enhances project efficiency through AI assistant development.

Critically, the DISOPs system operates outside of GxP workflows—functioning as a pre-GxP training tool—while being built for full transparency and audit-readiness as organizations approach compliance requirements like 21 CFR Part 11. The platform currently runs on Google's Gemini API, with options for cloud-based client silos or fully local deployment to protect sensitive intellectual property.

Richard and David also address pressing concerns around data privacy and IP ownership. Using Google's API allows organizations to opt out of model training on their data, and existing case law generally supports the position that human-edited, system-maintained content remains owned by the individual or organization that created it.

DISOPs itself is a life sciences-specific customization of PAIR, PICLLC's underlying AI framework, tailored to meet the unique regulatory and operational demands of the industry.

Be on the lookout for Parts 2 and 3 of this interview!

Editor's note: This transcript is a lightly edited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.



My name is Richard Jaenisch. I am the senior director of Education, Outreach, and Digital Experience at Open BioPharma Research and Training Institute in Carlsbad, California.

I am David Jaenisch. I am the director of technology at Prompting Integration and Consulting LLC, PICLLC for short.

So for the most part, human AI training parallelization will is just effectively parallelyzing whatever system you're already deploying. So generally speaking, it is functionally what you are already doing, but it's enabling AI in the specific components in the workflow where it is pertinent. And so it really depends on whatever AI deployment you're using.

So in that concept, conceptually, for the for that system, it really depends on what you're using. In our case, what we're using is DISOPs, or digitally interactive SOPs, as well as using another piece, of basically Gemini.

But what we are doing though is not in the GxP workflow. So in this case, it's very external because it's all pre-GxP. So in this case, it isn't really hitting that area just because it's mostly on the research side in terms of what we've deployed. We are getting to the point now where we're actually entering 24 CFR Part 11.

However, DISOPs as a program, while its name does imply that it is interacting with the SOPs, it is external. So the idea is that it's taking the SOP, taking the materials that you're working with and putting them all together into one system, and that system is entirely transparent. So it can go through, it can be validated through any method that's already in play. But the thing is, it's generally not as part of your GxP component. So it's more of the training element. So usually if you have a situation where you need to have retraining, where you need to have that, correction, then this is an opportunity to be able to use that.

And then in that sense, you have a completely transparent record of not only the training itself, but how the exact training was deployed. So the benefit of the tool is that it is completely transparent in its entire methodology.

So it is awkward for a generative AI tool to have that, but because of the method of how it breaks down each component and where the actual user specifically has the articulate control of the components, all of that produces a digital record that can then be audited at any time.

In terms of how our product works, we currently work with Gemini on the cloud. It can technically work with any cloud computing instance, but it can also run locally. So if your concern predominantly is about IP theft, locally will obviously make that literally impossible. And if you are running it on the cloud, we create silos for each of our individual customers, so that way they are completely separate from any other client, and there will be no data sharing between them.

If your concern is predominantly about the idea of the model being trained on it, Google explicitly allows you to disable this functionally when you use the API. Certain API use, they allow you to just say, "I'm not training on this." This is also true for their enterprise client. To my knowledge, it's not true for Open AI currently, due to an ongoing lawsuit with The New York Times. I'm not 100% sure about that. Don't quote me on legal.I don't know legal. What this means is you're safe from the perspective of Google getting anything from you or from other companies as well.

And in terms of ownership of IP, that is a complex ongoing legal question in terms of generated content in general. However, Google definitely doesn't own it. Yes. We've decided that. It is either, no one or it is the company, depending on the situation and level of editing. And because these are edited after the fact and they are maintained within a system that's maintained by people and turned into a holistic list of questions, I believe that it would be more likely they'd be owned by the person making them as opposed to being un-copyrightable in that case.

Generally speaking, there have been court cases so far that explicitly state that the human owns the copyright, not the AI tool. So anything generated is generated by an individual, that individual who created the system. And our system is done in such a way that it would not be in that same facet.

But I will say this though, the project-based component of project-based human AI training parallelization on the project's basis, that is owned by the process owner. So whoever the process owner has that IP of whatever the project is and how that's developed, that is a separate contract and a separate system that we generally do at Open BioPharma. And so we have those types of projects that are deployed frequently from time to time. And so in that case, those are deployed and owned by the process owner, which is typically the company we work with. Although occasionally there is a partnership collaboration of some kind.It's not usually a straight partnership. It's usually a situation where IP is developed and there's a lot of discussion around how that works. That being said, that is project-based, and so it's very unique in that way.

The DISOPs component is what David is speaking to. And so those elements, he's talking specifically as PICLLC created PAIR, which is basically the underlying layer of DISOPs. So DISOPs is a customized version of PAIR built specifically for life sciences to handle the unique situations that occur within life sciences. Just so I have some clarification on those pieces.

Videos

Olon at DCAT 2026 | Created with Canva - Image courtesy of Olon

, Olon is presenting its 2026 development plan, which spans investments across four countries: the United States, India, Italy, and France.

 The plan offers a detailed picture of where the company is directing its capacity and capabilities over the coming year.

Paolo Tubertini, chief executive officer, Olon, said in a press release,

 "Our strategy is focused on expanding capabilities that are critical for the development of complex therapies and sustainable manufacturing, combining innovation with operational excellence across key technology platforms."

Where Are the Most Significant Capacity Changes Happening?

The expansion with the clearest near-term implications for drug development teams is in France, at the Saint-Julien site, where a new bioprocess development suite is nearing completion.

 The facility is designed to support upstream and downstream development and scale-up of recombinant proteins, including monoclonal antibodies in complex formats and antibody–drug conjugates. A multi-purpose suite at the same site will double bioconjugation capacity, supporting both clinical and commercial manufacture.

This investment connects directly to earlier infrastructure work at the Rodano site in Italy, where Olon has developed payload and linker synthesis capabilities.

 Together, the two sites are intended to cover the full manufacturing chain for antibody, drug conjugates, from toxin and payload production through conjugation and final drug substance. The ability to manage that entire sequence within a single organization reduces coordination risk and simplifies regulatory documentation.

Maurizio Sartorato, vice president of the BioTech Division, Olon, noted in the press release,

 "The expansion of capabilities across multiple sites, together with the progress at Saint-Julien and the continued strengthening of our operations in Italy, supports greater flexibility in managing development and scale-up activities for complex therapies."

In Italy more broadly, current investments target high-potency API manufacturing and chemical synthesis, alongside an expansion of microbial fermentation capacity to support biologics and complex therapy programs.

 These are areas where manufacturing slot availability and technical depth remain frequent constraints for development organizations, particularly those moving candidates from phase II into late-stage or commercial production.

In India, the focus is on expanding API production capacity to strengthen supply continuity, a consideration that has taken on renewed importance for companies managing global supply chains.

 In the US, Olon is directing resources toward scale-up and integrated manufacturing capabilities, reinforcing its footprint for clients who require domestic or nearshore options as part of their supply strategy.

The 2026 plan also encompasses investments in sustainable protein production and green biocatalysis, areas increasingly relevant to organizations whose development pipelines intersect with regulatory and corporate expectations around environmental performance.

 These are not peripheral initiatives; they are being pursued at industrial scale, reflecting a practical rather than aspirational approach to greener manufacturing processes.

How Does Olon's Sustainability Work Connect to Its Manufacturing Strategy?

The green biocatalysis work referenced in Olon's 2026 plan has taken a concrete form through a recently announced partnership with myBIOS, an Austrian biotechnology company specializing in methanol-free Pichia pastoris fermentation.

 Conventional recombinant protein production using this microorganism relies on methanol induction. This process typically carries safety, regulatory, and environmental complications. The collaboration introduces myBIOS' myPichia platform, which replaces methanol with non-toxic inducers while maintaining comparable protein yields. This translates to simpler regulatory documentation and reduced site safety requirements during fermentation. Olon brings over 30 years of recombinant protein production experience to the partnership, providing the industrial infrastructure needed to move the platform beyond laboratory scale.

Olon SpA. Olon advance global expansion and sustainable biomanufacturing expertise at DCAT New York. Rodano (MI, Italy): Olon SpA; 2026. Press release.

Olon SpA. Olon and myBIOS partner to advance sustainable methanol-free protein production. Rodano (MI, Italy): Olon SpA; [cited 2026 Mar 24]. Available from: 

https://olonspa.com/news/olon-and-mybios-partner-to-advance-sustainable-methanol-free-protein-production/

Olon’s 2026 development plan allocates capital across the US, India, Italy, and France to expand capabilities for complex therapies and greener manufacturing. France’s Saint‑Julien site is nearing completion of a bioprocess development suite for recombinant proteins and a multipurpose area doubling bioconjugation for ADCs. Rodano, Italy, strengthens payload and linker synthesis to create an integrated ADC chain. Additional Italian projects increase HPAPI, chemical synthesis, and microbial fermentation. India expands API capacity; the US emphasizes scale-up and integrated manufacturing. A myBIOS partnership advances methanol-free Pichia protein production.

Olon is expanding global biologics and high-potency manufacturing capacity across four countries, with major ADC chain investments completing in 2026.

What Olon Is Building for Complex Therapy Manufacturing in 2026

Partha S. Anbil is a cognitive enterprise transformation leader (partha.anbil@ibm.com) with IBM’s Healthcare and Life Sciences practice.

Hybrid Cloud Architecture | Created with Canva

Pharmaceutical and biotechnology organizations face an unprecedented dual mandate: accelerate innovation through advanced data-intensive technologies while maintaining compliance with the world's most stringent regulatory frameworks. Hybrid cloud architecture has emerged as the strategic solution to this challenge, combining the scalability and innovation of public cloud with the control and security of private infrastructure. With the life sciences cloud computing market capturing its largest share through hybrid deployments in 2024 and projected to maintain this leadership through 2034, this architectural approach has become fundamental to pharmaceutical operations.

This article examines how hybrid cloud architecture enables pharmaceutical companies to navigate the complex landscape of drug discovery, development, manufacturing, and commercialization. We explore the regulatory imperatives of driving hybrid adoption, analyze proven deployment patterns across the pharmaceutical value chain, and demonstrate how leading organizations leverage this model to accelerate time-to-market while ensuring data integrity, intellectual property protection, and regulatory compliance.

How Does the Industry Navigate Complex Regulatory Requirements?

The pharmaceutical industry operates under an intricate web of regulations that creates unique infrastructure challenges. The FDA's 21 CFR Part 11 governs electronic records and signatures, while Good Practice (GxP) quality guidelines impose strict requirements for data integrity, auditability, and control across all phases of pharmaceutical production.

The globalization of clinical trials and supply chains further introduces international data sovereignty laws that dictate where and how patient data can be stored and processed.

Recent regulatory developments have intensified these infrastructure requirements. The FDA's January 2025 draft guidance on AI and Machine Learning in drug development, combined with the joint FDA-European Medicines Agency guiding principles released in January 2026, emphasizes model governance, data lineage, and transparency of AI-driven decision-making.

 The joint FDA-EMA framework establishes ten guiding principles for AI in drug development, including:

Human-centric design with appropriate oversight

Risk-based approaches proportionate to impact

Adherence to quality management and regulatory standards

Clear context of use and limitations documentation

Multidisciplinary expertise in development and deployment

Robust data governance and documentation practices

Rigorous model design and development methodologies

Risk-based performance assessment and validation.

Comprehensive life cycle management protocols

Clear essential information for regulatory review

These requirements necessitate infrastructure offering complete visibility and control—capabilities more readily achieved in hybrid environments than pure public cloud models.

How Can Organizations Use Hybrid Cloud to Protect Their Intellectual Property and Competitive Advantage?

Hybrid cloud architectures are becoming foundational in pharma and biotech by balancing public-cloud elasticity with private, single-tenant control needed for GxP, 21 CFR Part 11, and data sovereignty. Evolving FDA and joint FDA-EMA expectations for AI/ML—model governance, traceability, validation, and lifecycle management—further favor environments with strong visibility and auditability. Common deployment patterns include data-residency tiering, federated learning, and cloudbursting for compute peaks. Value is demonstrated across discovery, clinical trials, manufacturing (Pharma 4.0), supply chain, and regulatory submissions via a risk-based, graduated adoption model.

Hybrid cloud architecture enables pharma organizations to balance public cloud scalability with private infrastructure control, accelerating drug development while maintaining regulatory compliance.

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