In this fourth annual exclusive Leadership Panel discussion, Drug Development & Delivery life science leaders discuss the role of AI in drug repurposing, the future of personalized medi­cine, the importance of sustainability, and how to keep pace with innovation amid real-time FDA reviews. This year’s roundtable leaders are: Paul O’Shea, CSO, Exemplifyy BioPharma (a Symeres company); Dr. David Butler, Chief Technology Officer, Hongene; and Rick Seibert, CIO, SVP, Corporate Technical Services, Sharp.

AI & DATA ANALYTICS INTEGRATION WILL BE PERVASIVE IN DRUG DISCOVERY & INNOVATION

Mr. O’Shea: AI and data analytics are becoming foundational to modern R&D, particularly as drug discovery programs are increasingly divided into smaller, faster-moving stages. Quality data is more important than ever, and organizations are relying on digital tools to generate insights from limited early-stage experiments and to inter­pret those outputs in ways that guide funding decisions and downstream development. The growing value of AI lies in its ability to uncover patterns that human assessment alone might miss. Whether in complex solid-state screening datasets, process optimiza­tion studies or early risk-assessment exercises, AI-guided processes can help shape an investigational new drug (IND)-enabling strategy.

The industry is also recognizing that digitalization must be paired with scientific context. Although AI can ac­celerate decision-making, scientists are still required to interpret what the data means for regulatory expecta­tions, impurity control or next-step technical design. With the develop­ment of innovative modalities, including lipids, radioligands, and polymer-based delivery systems, the volume and complexity of datasets will continue to expand. This makes se­cure, compliant data management and AI-enabled insight generation in­tegral to faster and more flexible drug discovery and development.

Dr. Butler: AI and data analytics are increasingly being embedded in early drug discovery workflows. This is par­ticularly prevalent in modalities such as RNA therapeutics, where sequence space, delivery optimization, and manufacturability each present multi­dimensional challenges. We expect AI integration to become increasingly prevalent across early discovery, can­didate optimization, and manufac­turability prediction. For RNA modalities, AI models are already ac­celerating sequence design, second­ary structure prediction, and predictive modeling of innate immune activation or off-target motifs. They are also be­ginning to support LNP formulation optimization, helping teams reduce experimental complexity and focus on the most promising candidates.

Equally important is AI’s role in developing and innovating CMC with the implementation of digital systems that continuously capture process data across manufacturing operations. These datasets create opportunities for AI-assisted yield prediction, impurity tracking, and automated process op­timization, which may shorten devel­opment cycles and improve batch-to-batch consistency.

As the industry moves toward higher-volume oligonucleotide and mRNA products, AI will allow compa­nies to make data-driven decisions about scalability, cost of goods and sustainability. Rather than being a spe­cialized tool, AI is likely to become in­creasingly integrated across the pipeline, from discovery to commer­cial manufacturing, where it can sup­port faster innovation and improved patient outcomes.

Mr. Seibert: AI is rapidly reshaping how drug discovery and innovation occur, and that shift will ripple across the entire pharmaceutical supply chain – including CDMOs. As pharma companies adopt AI to accelerate early-stage discovery, they will increas­ingly expect their downstream part­ners to operate with a similar level of intelligence—delivering faster insights, higher-quality outputs, and more con­nected operations across the value chain.

In the CDMO environment, AI is already providing high-value predictive insights. By evaluating historical per­formance and real-time operational data, AI can forecast demand, optimize inventory, and recommend the most ef­ficient production schedules. This en­ables both CDMOs and their clients to respond faster, use resources more ef­fectively, and drive higher overall throughput and reliability.

Given the pace of advancement, AI’s role within CDMOs is expected to grow exponentially – moving from op­erational support into increasingly so­phisticated applications that enhance quality, efficiency, and innovation across the full development lifecycle.

However, as industry moves to­ward increased automation and intel­ligence, maintaining strong human oversight will be essential. The phar­maceutical industry operates in a highly regulated environment, where quality, data integrity, and patient safety cannot be compromised. AI-dri­ven insights must be validated, inter­preted, and governed by experienced professionals who understand regula­tory expectations and can ensure sys­tems are used compliantly. Human review of AI recommendations – particularly those affecting product qual­ity, batch disposition, and regulatory submissions – will remain critical in this transition. CDMOs that strike the right balance between leveraging AI and preserving expert human judg­ment will be best positioned to adopt these technologies responsibly and ef­fectively.

AI WILL BE ESSENTIAL IN DRUG REPURPOSING

Mr. O’Shea: By rapidly interpreting preclinical observations, solid-state behavior, analytical trends, impurity profiles, and historical performance across related chemistries, AI can help significantly accelerate drug repurpos­ing. These tools help teams recognize when a molecule with setbacks in one program may hold promise else­where, enabling the swift pivots that are increasingly essential in early de­velopment. Data interpretation sup­ported by AI gives sponsors faster clarity on feasibility, regulatory impli­cations and the most efficient path to­ward new IND submissions.

Drug repurposing itself is gaining traction because the economic and geopolitical climate is pushing organ­izations toward lower-risk discovery and development models. Developers are dividing programs into smaller and more achievable milestones. When a candidate falters, the ability to rapidly slot in a new molecule or redirect an existing one protects budg­ets and timelines. Strategic partners with deep scientific breadth can help translate AI-generated insights into practical next steps, ensuring teams understand what the data means for manufacturing, formulation and clini­cal-trial readiness. As reshoring pres­sures, cost constraints, and diverse modality pipelines grow, repurposing offers a path to resilience in drug dis­covery and development.

Dr. Butler: AI is transforming drug re­purposing by enabling rapid, large-scale interrogation of large biological and clinical datasets to identify new therapeutic hypotheses for repurpos­ing existing molecules. Machine Learning models can help detect dis­ease-target associations, mechanistic overlaps, transcriptomic signatures, and real-world evidence patterns that would be difficult to identify at scale. As these tools mature, they are poised to accelerate the repurposing cycle while reducing uncertainty and cost.

Repurposing continues to attract interest because it aligns with the in­dustry’s need for speed, reduced de­velopment risk, and capital efficiency. Existing molecules carry known safety profiles, allowing developers to by­pass years of toxicology studies and move directly into proof-of-concept tri­als. As development timelines shorten, payers become more demanding and clinical expectations rise, the ability to move forward with fewer unknowns makes repurposing a pragmatic path to both clinical and commercial im­pact.

AI amplifies this value across mul­tiple points in the development process, from identifying unexpected therapeutic opportunities to support­ing work on optimizing dosing and patient stratification. For nucleic acid therapeutics, AI-driven transcriptomic and pathway analyses are beginning to surface new genetic targets that pair well with established delivery plat­forms, opening up opportunities for both novel indications and repur­posed mechanisms.

PERSONALIZED MEDICINE WILL ADVANCE AS CELL & GENE THERAPIES SCALE FROM NICHE TREATMENTS TO BROADER PLATFORMS

Dr. Butler: As cell and gene therapies (C&GTs) mature into scalable plat­forms, we believe that personalized medicine is evolving from bespoke in­terventions into modular, accessible therapeutic systems. Standardized manufacturing solutions and compo­sitional and delivery innovations will enable developers to move beyond one-patient-at-a-time manufacturing toward indication- and genotype-spe­cific product architectures.

For nucleic acid technologies (NAT), this shift is especially powerful. Oligonucleotides and mRNA already permit sequence-level customization, allowing rapid redesign for individual specific mutations or defined patient subgroups without reinventing the en­tire manufacturing process. As process technologies advance, a larger num­ber of “n-of-1” therapies may become feasible in defined contexts, with far greater consistency, lower cost, faster turnaround times, and greater consis­tency than today’s bespoke ap­proaches.

At Hongene, we are investing di­rectly in this future. In collaboration with leading innovators, we are build­ing a dedicated oligonucleotide syn­thesis suite to support personalized and ultra-rare genetic disease pro­grams. In parallel we are advancing our HiXCap™ cap analog technology to the clinic to enable more potent and durable mRNA personalized cancer vaccines (PCVs). Together, these capa­bilities position us to help partners de­liver personalized medicines at a scale and speed that were previously unat­tainable.

Ongoing advances in bioinfor­matics, patient stratification, and targeted delivery are helping to further strengthen this trajectory. Simultane­ously, emerging tools, such as tissue-specific LNPs, antibody-oligonucleotide conjugates, and next-generation cap analogs and nucleotides, enable drugs to be tuned to both the disease and relevant organ system.

As C&GT platforms become more scalable, these developments are making personalized medicine more accessible by reducing cost of goods sold (COGS), improving manufactur­ing resilience and facilitating regula­tory harmonization, turning what were once niche therapies into viable global interventions.

A CONTINUED FOCUS ON SUSTAINABILITY INITIATIVES

Mr. Seibert: Regarding corporate ini­tiatives, sustainability has become one of the pillars of our strategy over the last several years. We see it as a pos­itive force for innovation and collabo­ration. Sharp recognizes that there is an immediate need for action to ad­dress the threat of climate change and that action must be embedded in a data-driven, science-based methodol­ogy. Establishing SBTi targets for our organization became a key objective of our sustainability strategy in 2025. Our targets were validated in July, marking a significant step in our jour­ney to reducing our environmental im­pact and contributing to a more sustainable future.

As a CDMO, Sharp operates in a highly interdependent way with clients and our own supplier network, and we recognize that the scale of carbon re­ductions required will not progress fast enough without broad and significant cooperation across that network.

While we need to ensure our Scope 1 & 2 emission reductions re­main on track, Scope 3 is the predom­inant challenge for most organizations and collaboration is the cornerstone to progressing Scope 3 in the pharma supply chain.

As part of our clients’ Scope 3 emissions, it’s clear that we need to focus on our carbon reduction plan­ning to enable them to achieve their own SBTi goals. Once we achieved validation of our SBTi targets in July, our focus immediately moved to es­tablishing measurable, year-on-year actions that will drive overall progress towards reaching our SBTs. The roadmap to deliver this progress is a Climate Change Transition Plan for our operations that outlines the path­way to achieving our Near- and Long-Term targets.

We are making progress on the energy-efficiency initiatives already underway and have assessed energy consumption at our facilities with the aim of improving current sustainability performance. We are considering the impact of, for example, moving to more energy-saving measures, such as LED lighting, more efficient HVAC selection, optimized heating and cool­ing settings, motion sensor lighting, etc. We are making plans to improve our waste management processes at our facilities to maximize reuse and recycling of waste materials, while avoiding landfill and decreasing incin­eration where possible. These imme­diate actions will support both our interim milestones and our long-term net-zero ambition.

As with many companies in the supply chain, we need to deepen our sustainability reporting processes by collaborating more closely with our own suppliers to capture their carbon emissions data, to increase trans­parency, and identify opportunities for shared reductions. This visibility is es­sential, not only for achieving our own SBTi pathway but also for contributing positively to our clients’ climate goals. No entity or organization will be able to transition independently at the re­quired speed or scale to successfully reach their climate goals.

As a CDMO, and experts in the assembly, labeling, and packaging of pharma products, we also recognize the important role we play in acceler­ating the identification and qualifica­tion of lower-carbon materials and processes. In 2023, we established our Sustainable Materials Innovation Group (SMIG) whose role is to deepen innovation efforts by identifying and validating new materials and designs for more sustainable pharma packag­ing. This multi-disciplinary group at Sharp recently published our Eco-De­sign Principles, which attempt to edu­cate and influence packaging design at the earliest stages of a drug launch, so together with our clients we can try to design as much waste and carbon as possible out of the drug packaging process.

Sharp is one of eight co-founders of the Alliance to Zero, whose main ambition is to facilitate the transition of pharma to net zero injectable de­vices. Each member company in the Alliance is committed to demonstrat­ing measured carbon reductions within its own operations as part of its sustainability goals. The Alliance offers a collaborative forum for sharing best practices, research, and innovation through pragmatic solutions that can be applied directly to improving each company’s GHG emissions.

Dr. Butler: At Hongene, sustainability is a design principle shaping our fa­cilities, processes, and partnerships. We are committed to achieving car­bon neutrality by 2030 while expand­ing the capacity required to meet global demand for RNA therapeutics. To support this ambition, we have incorporated renewable-energy infra­structure, including 100% solar-pow­ered exterior lighting and electric vehicles for on-site logistics and in­vested in solvent-recycling systems that reduce organic-waste generation.

Hongene’s foundation in bio­catalysis underpins our commitment to sustainable innovation, and our chemoenzymatic ligation platform ex­emplifies how advanced technology can enhance both efficiency and envi­ronmental responsibility. By delivering higher yields and reducing solvent consumption, this approach enables a greener and more scalable route to siRNA, sgRNA and other oligonu­cleotides. Additionally, as a vertically integrated one-stop CDMO, we fur­ther minimize environmental impact by consolidating raw material produc­tion and RNA manufacturing under one roof, cutting transportation needs and reliance on third-party suppliers.

We measure environmental progress through third-party ESG as­sessments, including our recent Eco­Vadis Bronze Rating, and continue to partner with organizations such as the ACS Green Chemistry Institute to ad­vance industry-wide best practices. These efforts ensure sustainability re­mains embedded in both Hongene’s operations and the broader NAT man­ufacturing ecosystem.

5. REAL-TIME FDA REVIEWS AND PLATFORM-LEVEL DESIGNATIONS WILL INFLUENCE HOW COMPANIES KEEP PACE WITH INNOVATION

Dr. Butler: Real-time FDA review path­ways and platform-level designations, such as Advanced Manufacturing Technology (AMT), represent a shift to­ward regulatory models designed to support innovation, quality and digital readiness. For NAT, these frameworks might support earlier adoption of op­timized manufacturing platforms, such as enzymatic oligonucleotide synthesis or high-efficiency mRNA production, into clinical and commercial use.

For companies like Hongene, these developments further encourage investment in scalable, well-character­ized, digitally monitored manufactur­ing systems. Building on this foundation, the implementation of continuous data capture, advanced analytics, and automated process controls can help support customers seeking platform-level regulatory strategies.

These FDA initiatives will also ele­vate expectations for process trans­parency and change-management discipline. Manufacturers that can demonstrate statistical control, digital traceability, and sustainability advan­tages are more likely to move faster through regulatory pathways.

Real-time review and platform designations can help compress de­velopment timelines and allow inno­vative technologies to reach patients sooner. They signal a future in which regulatory speed is directly linked to technological maturity, encouraging companies to modernize proactively rather than reactively.