How Abzena Uses AI and Data-Driven Tech to Accelerate Biotech Solutions for Patients
A leading bioconjugate and complex biologics CDMO/CRO, Abzena is advancing the frontiers of biotech by combining discovery, development, and manufacturing with a data-driven approach. The company emphasizes end-to-end programs that de-risk and streamline development, supporting patients in need by delivering faster, smarter pathways from concept to commercial launch. At the heart of this transformation is a commitment to leveraging automation, AI, and rigorous data strategy across its global network of facilities, ensuring that every step—from early research to GMP manufacturing—is informed by robust analytics and aligned with regulatory requirements. This article delves into how Abzena integrates technology with biotech know-how, the leadership driving this strategy, and the concrete implications for clients and patients.
Abzena’s end-to-end capabilities and business model
Abzena positions itself as a full-spectrum partner for the biopharmaceutical industry, specializing in bioconjugates, antibody-drug conjugates (ADCs), and complex biologics. The company operates as both a CDMO (Contract Development and Manufacturing Organization) and a CRO (Contract Research Organization), providing a continuum of services that span discovery, preclinical development, process development, scale-up manufacturing, analytical support, and ultimately readiness for commercial launch. This integrated approach is designed to de-risk the development timeline for clients who require not only scientific expertise but also seamless project management, quality control, and regulatory compliance.
From discovery through commercialization, Abzena offers fully integrated programs that can be tailored to the needs of individual projects. The emphasis is on delivering end-to-end solutions rather than isolated services, a strategy that reduces handoffs, accelerates decision-making, and enhances program visibility for sponsors. By consolidating activities under one umbrella, the company can optimize resource allocation, harmonize data streams, and coordinate cross-functional teams to maintain a cohesive development tempo. Clients gain access to a unified project plan, consolidated risk assessments, and a single point of accountability, which are critical when navigating the complexities of bioconjugate therapeutics and complex biologics.
Central to Abzena’s value proposition is the push to de-risk development through proactive design choices, rigorous quality systems, and continuous optimization. De-risking in this context means minimizing the likelihood of late-stage failures, manufacturing-scale challenges, or regulatory hurdles that could derail a program after significant investment. Abzena achieves this by integrating early-stage feasibility studies with robust process development, scalable manufacturing, and applicable regulatory readiness from the outset. This proactive stance helps clients anticipate potential bottlenecks, adopt mitigation strategies early, and maintain momentum toward clinical and market milestones.
Among the core capabilities is the execution of Good Manufacturing Practice (GMP) and current good manufacturing practice (cGMP) operations across a geographically diverse network. Abzena’s global footprint includes facilities in San Diego, California, and Bristol, Pennsylvania, in the United States, as well as Cambridge in the United Kingdom. These locations provide a mix of wet-lab biochemistry, process chemistry, analytics, formulation development, and manufacturing capabilities, enabling end-to-end operations across different therapeutic modalities and scales. The distribution of capabilities across multiple sites supports redundancy and capacity planning, while also enabling proximity to major biopharma clusters, academic collaborations, and regulatory ecosystems.
The integration of discovery and development workflows with manufacturing is reinforced by a data-driven culture. Abzena’s leadership emphasizes the critical role of data in automation, drug discovery, and accelerated outcomes. Data-backed decision-making helps to optimize candidate selection, design of experiments (DoE), process parameters, and quality controls. By aligning data governance with regulatory expectations, the company ensures traceability, reproducibility, and auditable records, all of which are essential for successful regulatory submissions and clinical development programs.
A distinctive feature of Abzena’s model is its dual offering: fully integrated programs designed to deliver end-to-end outcomes, and modular services that address specific needs within a project. This flexibility is valuable to sponsors who may already have certain capabilities in-house or require specialized expertise in a particular domain, such as bioconjugation chemistry, ADC linker technology, or complex biologics formulation. The ability to scale from a single experimental service to a comprehensive development program enables Abzena to adapt to evolving project requirements while maintaining consistency in quality and operational efficiency.
In terms of therapeutic scope, Abzena’s focus on bioconjugates and ADCs places it at the intersection of targeted therapy and precision medicine. Bioconjugates combine biological molecules with chemical moieties to enhance therapeutic delivery, specificity, and efficacy. ADCs, in particular, rely on precise linker technology, stable conjugation, and controlled release mechanisms to maximize anti-tumor activity while minimizing off-target toxicity. Complex biologics involve large, multifunctional proteins or fusion constructs that require sophisticated analytical methods and robust manufacturing processes. Abzena’s capabilities in these areas mean it can support programs that demand intricate chemistry, advanced analytics, and rigorous quality assurance across development stages.
For clients, the practical upside of this business model is clearer timelines, improved predictability, and a tighter alignment between scientific strategy and manufacturing readiness. Early-stage feasibility studies can be tied directly to scalable process development plans, which reduces the risk of late-stage delays. The end-to-end approach also enhances program governance, enabling higher levels of oversight, milestone-based progress tracking, and transparent cost management. In addition, the global facilities network supports continuity of supply and the ability to respond to shifting demand, regulatory expectations, and evolving client needs.
The ability to deliver “from discovery through commercial launch” is particularly meaningful in the context of ADCs and complex biologics, where development timelines are often lengthy and complex. By coordinating activities across multiple disciplines—biochemistry, proteomics, pharmacokinetics, toxicology, formulation science, analytics, and regulatory affairs—Abzena helps ensure that knowledge gained at each stage informs subsequent decisions. This feedback loop is critical for maintaining a steady project velocity and aligning scientific innovation with practical manufacturing feasibility.
From a client perspective, the end-to-end model translates into a simpler vendor landscape, fewer compatibility concerns between disparate teams, and a more coherent integration of process development with clinical manufacturing timelines. It also places a premium on robust data capture, harmonization of measurement standards, and the use of analytics to forecast outcomes, optimize resource allocation, and monitor early indicators of program health. All of these elements come together to create a development ecosystem that is not only scientifically rigorous but also operationally efficient and regulatorily compatible.
The broader industry context is one of increasing demand for more flexible, integrated, and technology-enabled biopharmaceutical development services. Bioconjugates and ADCs present unique challenges that require specialized chemistry, analytical rigor, and manufacturing sophistication. Abzena’s integrated programs are designed to address these challenges by providing a cohesive platform that captures the synergy between discovery science and manufacturing execution. The combination of scientific depth, manufacturing discipline, and data-driven management positions Abzena as a partner capable of accelerating innovation while maintaining high standards of quality, safety, and patient-centered outcomes.
As the biotech ecosystem evolves, the emphasis on patient impact remains a central driver for Abzena. The company’s development philosophy centers on delivering therapies that address unmet medical needs with faster timelines, while maintaining stringent risk management and quality practices. By aligning scientific ambition with practical execution, Abzena aims to shorten the path from laboratory insight to patient access, a goal that resonates across biopharma, academia, and patient advocacy communities. In sum, Abzena’s end-to-end capabilities, global footprint, and data-centric approach create a robust framework for advancing next-generation therapies in a complex and competitive market.
The role of cGMP and compliance in a global development program
A robust compliance framework underpins Abzena’s operations, ensuring that every stage of development adheres to regulatory expectations and quality standards. The company’s cGMP capabilities span the essential operations required for therapeutic development, including manufacturing, process validation, quality control, and documentation practices that support regulatory submissions. Across the US and UK sites, teams implement standardized quality systems, validated analytical methods, and rigorous batch records to ensure traceability and reproducibility. Compliance is not a static requirement; it is an ongoing discipline that informs decisions from process development to commercial manufacturing, and it is integral to maintaining confidence among sponsors and regulators alike.
Within a global program, harmonization of quality systems and standard operating procedures is critical. Abzena emphasizes cross-site alignment to ensure consistent performance, even as facilities operate with regional differences in regulatory expectations or resource constraints. This harmonization supports scalable production, robust change management, and uniform consequence analysis when deviations occur. It also reinforces the reliability of data across sites, enabling more accurate program-level analyses and forecasting. In practice, this means that data generated at the San Diego site, the Bristol site, or the Cambridge facility can be integrated seamlessly into a single, auditable dataset that informs decisions across the entire development lifecycle.
Moreover, the integration of regulatory science into the development process helps anticipate and resolve potential hurdles before they arise. Early discussions with regulatory authorities, alignment of pharmacovigilance plans, and development of risk-based quality control strategies all contribute to smoother inspections and approvals. For patients and sponsors, this translates into a more predictable regulatory path, fewer surprises during audits, and a higher likelihood of meeting clinical and commercial milestones.
In summary, Abzena’s end-to-end model is anchored in a strong compliance framework that scales with the program. The combination of cGMP manufacturing, rigorous analytics, and cohesive quality systems across multiple geographies provides a robust foundation for delivering complex biologics and ADCs from concept to clinic and beyond.
Leadership at the intersection of data, technology, and biotech
Dave Williamson, the Chief Information Officer at Abzena, sits at the nexus of technology strategy, data governance, and operational excellence. With a background rooted in chemistry and a rich career spanning pharma, generics, and biotech, Williamson brings a unique blend of scientific intuition and information technology leadership to the company. His professional journey began after completing university studies funded by the US Army, an experience that broadened his horizons and enabled him to travel the world. That exposure fostered a long-standing curiosity about how science works in diverse environments and how technology can enable better outcomes in healthcare.
Williamson’s chemist’s mindset informs his approach to biotech IT strategy: he believes that data, when properly harnessed, can illuminate the path from discovery to patient impact. His view is that digital transformation is not merely about installing new software; it is about building a data-driven culture that supports scientific decision-making, accelerates experimentation, and reduces time to results. Over the years, he has accumulated extensive experience at the intersection of technology and health systems, contributing to progress across pharmaceutical development, generic drug manufacturing, and biotech innovation. This breadth of experience is particularly valuable in a company like Abzena, which must coordinate complex scientific workflows with stringent quality requirements.
As CIO, Williamson leads the company’s efforts to leverage automation and AI to speed outcomes while maintaining rigorous data integrity and compliance. He emphasizes the importance of a data-smart organization, where data capture is standardized, metadata is consistent, and analytics pipelines produce actionable insights that guide program decisions. Under his leadership, Abzena’s technology strategy is designed to integrate laboratory automation, data platforms, and advanced analytics in a way that aligns with the scientific goals of discovery, development, and manufacturing.
Williamson’s leadership approach reflects a deep commitment to training and talent development within the IT and data science teams. He recognizes that successful digital transformation requires not only sophisticated tools but also people who understand how to apply them in a biotechnology context. This involves close collaboration with scientists, engineers, and regulatory specialists to ensure that technology choices support experimental design, process optimization, and regulatory readiness. It also means cultivating a culture of continuous improvement, where incremental enhancements to data workflows, automation capabilities, and reporting dashboards cumulatively yield substantial gains in efficiency and reliability.
A core aspect of Williamson’s vision is the integration of automation and data across Abzena’s global facilities. Automation in the lab and manufacturing environments can reduce manual errors, increase throughput, and enable more consistent process outcomes. When paired with robust data platforms, automation provides real-time visibility into production performance, allowing teams to identify variances quickly, implement corrective actions, and verify that quality standards remain met throughout development and manufacturing. This combination of automation and data-driven oversight is particularly critical in ADC and bioconjugate programs, where precise control over chemical conjugation, linker stability, and product quality is essential.
Williamson’s narrative emphasizes that technology strategy must be aligned with patient-centric goals. He frames data initiatives as enablers of better patient outcomes through faster drug development timelines, more reliable manufacturing, and improved regulatory compliance. In practice, this means prioritizing projects that shorten the distance from bench to bedside, while ensuring that safety and efficacy remain at the forefront. It also means building scalable systems that can adapt to evolving scientific methods, regulatory expectations, and market dynamics without compromising data integrity or operational performance.
In summary, Dave Williamson’s leadership embodies the fusion of scientific curiosity, operational discipline, and digital maturity. His role as CIO centers on enabling Abzena to navigate the increasingly data-driven landscape of biotech, where AI, automation, and analytics are essential tools for accelerating discovery and delivering therapies to patients. By fostering a data-smart culture, promoting cross-functional collaboration, and driving the adoption of robust IT and automation platforms, Williamson helps position Abzena as a forward-looking partner capable of transforming complex programs into tangible patient benefits.
The science-technology interface in practice
A recurring theme in Williamson’s narrative is the notion that technology should amplify scientific insight rather than replace it. In practical terms, this means deploying AI and machine learning to augment researchers’ ability to design experiments, interpret results, and optimize manufacturing workflows. The interface between science and technology at Abzena involves carefully curated data sources, standardized data models, and interoperable analytics tools that can accommodate diverse experimental modalities, including bioconjugation chemistry, antibody engineering, and biologics formulation.
For example, in the early phases of a program, AI-driven design of experiments can help identify the most informative experiments to run, thereby reducing the time and resources required to map critical process parameters. In later stages, predictive analytics can forecast batch behaviors, anticipate variability in raw materials, and guide process optimization efforts. Across manufacturing, digital twins and simulation-based planning can support scale-up decisions, enabling engineers to model the impact of parameter changes on product quality and yield before implementing them in the real world. The result is a more iterative and data-informed development process that preserves scientific rigor while accelerating progress.
Williamson’s approach also emphasizes governance and risk management when adopting new technologies. Given the regulatory requirements that govern biotech development, any AI model or automation system must undergo rigorous validation, documentation, and traceability. Abzena’s data and computing landscape is designed to accommodate these needs, with validated data pipelines, auditable model lifecycles, and clear ownership for each data asset. This discipline ensures that AI-driven recommendations and automated decisions can withstand regulatory scrutiny and be reproduced across multiple sites and programs.
Finally, Williamson’s leadership highlights the importance of external engagement and industry dialogue. As a proponent of ongoing learning and collaboration, he supports participation in industry publications, conferences, and cross-sector initiatives that advance best practices in AI, automation, and digital transformation in biotech. This openness to collaboration helps Abzena stay at the cutting edge while remaining grounded in the practical realities of drug development and regulatory compliance.
AI and automation: Transforming Abzena’s drug development and manufacturing
AI and automation are central to Abzena’s strategy to accelerate bioconjugate and ADC programs. The company leverages these technologies to enhance discovery, development, and manufacturing, with a focus on delivering measurable improvements in speed, quality, and risk management. This section examines the practical applications of AI and automation across Abzena’s workflows, the benefits realized, and the considerations that accompany increased automation in a regulated environment.
AI-enabled discovery and design
In the earliest stages of a program, AI and machine learning can assist researchers in identifying promising targets, optimizing candidate molecules, and prioritizing experiments that maximize information gain. By analyzing vast datasets generated during screening, compound optimization, and early pharmacology studies, AI can reveal patterns that might escape traditional analysis. This supports more informed decision-making about which molecules to advance, which conjugation strategies are most likely to yield the desired therapeutic activity, and which linker technologies balance potency with safety.
At Abzena, AI-driven analytics can also facilitate SAR (structure-activity relationship) exploration for complex biologics and ADCs. By correlating molecular features with biological outcomes, researchers gain a deeper understanding of how modifications influence efficacy, stability, and immunogenicity. This knowledge is then translated into iterative design cycles that rapidly converge on lead candidates with favorable profiles. The result is a more efficient path from conceptual ideas to actionable development plans.
DoE and process optimization
Design of experiments (DoE) is a core methodology for understanding how process variables influence product quality. AI and automation enhance DoE by enabling more complex experimental designs, real-time data capture, and adaptive learning—where the system suggests subsequent experiments based on current results. This accelerates the optimization of critical process parameters in conjugation workflows, purification steps, and formulation development. The ability to systematically explore parameter spaces with high statistical confidence helps minimize variability and improve batch-to-batch consistency.
Automation complements DoE by standardizing execution. Robotic platforms and automated liquid handlers can perform thousands of micro-scale experiments with precision and repeatability. This not only speeds up data collection but also frees scientists to focus on interpretation and decision-making. The combination of AI-driven DoE and automated experimentation creates a virtuous cycle: more data leads to better models, which in turn guide more efficient experiments.
Analytics, quality, and regulatory readiness
In regulated environments, data quality and traceability are non-negotiable. AI is most valuable when it delivers reliable, interpretable insights that support decisions and are fully auditable. Abzena emphasizes validated analytics pipelines, version-controlled data models, and transparent model governance. AI outputs are complemented by human oversight and domain expertise to ensure that recommendations align with regulatory expectations and product quality requirements.
Quality control and quality assurance processes benefit from AI-enabled anomaly detection, trend analysis, and predictive maintenance for analytical instruments and manufacturing equipment. By monitoring performance, identifying drift, and preemptively addressing issues, Abzena can reduce the risk of out-of-specification (OOS) results and production delays. The regulatory dimension is critical: any AI tool must have documented validation, data lineage, and traceability to source data, with clear criteria for when human review is required. This ensures that AI contributes to, rather than complicates, the regulatory narrative for clinical and commercial programs.
Digital twins and scale-up planning
Digital twins—virtual models of processes and production systems—are a powerful concept for scale-up planning in ADC and bioconjugate manufacturing. They allow teams to simulate how changes in process parameters affect product quality and yield, anticipate potential bottlenecks, and optimize manufacturing steps before implementing changes in the real world. For Abzena, digital twins enable faster, more reliable scale-up from laboratory to pilot to commercial manufacturing, reducing the risk of surprises that can derail timelines or quality.
Data governance and cross-site integration
As AI and automation proliferate across multiple sites, robust data governance becomes essential. Abzena’s strategy emphasizes standardized data formats, metadata schemas, and interoperable data platforms that ensure data generated at San Diego, Bristol, and Cambridge can be integrated into a single, coherent analytics workflow. This cross-site integration supports program-level insights, more accurate forecasting, and consistent quality metrics across the global enterprise. It also simplifies collaboration with clients, who benefit from a unified data story and clear visibility into program status and performance.
Challenges and considerations
The adoption of AI and automation in biotech comes with challenges. Data quality is foundational; models trained on inconsistent or incomplete data risk producing unreliable results. Validation and regulatory acceptance require rigorous documentation, transparent model governance, and auditable workflows. There is also the need to maintain a human-centric approach, ensuring that scientists remain central to decision-making and that automation serves as an enabler rather than a replacement for expertise. Finally, cybersecurity and data privacy must be prioritized to protect sensitive pipeline information and patient data throughout development and manufacturing.
Despite these considerations, the trajectory is clear: AI and automation have the potential to transform Abzena’s capabilities, enabling faster discovery, more robust process development, and greater manufacturing reliability. With disciplined governance, strategic investments, and a culture that blends scientific curiosity with technological sophistication, Abzena is positioned to accelerate therapeutic innovation while preserving the highest standards of quality, safety, and patient benefit.
Global facilities, client impact, and patient focus
Abzena’s global footprint is a strategic asset that supports its ability to deliver end-to-end programs across diverse therapeutic modalities and regulatory environments. The San Diego, Bristol (PA), and Cambridge (UK) sites collectively form a network capable of handling complex biologics, conjugation chemistry, analytics, and GMP manufacturing. This triad of locations provides geographic diversity, access to talent pools, proximity to key customers, and the capacity to execute integrated programs with a consistent quality framework.
The client impact of Abzena’s model is measurable in several dimensions. First, the end-to-end approach reduces the number of handoffs and interfaces that can introduce risk, delays, and miscommunication. By managing discovery, development, manufacturing, and regulatory readiness under one umbrella, Abzena offers sponsors greater project control and visibility. Clients can align milestones more precisely with corporate timelines and budget expectations, improving planning accuracy and reducing the likelihood of costly scope creep.
Second, the integrated model supports faster time-to-market for therapies that address pressing medical needs. The ability to move fluidly from discovery to early development to manufacturing with consistent data standards and quality controls helps shorten development cycles. This acceleration is especially valuable for ADC and bioconjugate programs, where the chemistry and biology must be tightly coordinated, and delays at any stage can have outsized effects on overall timelines.
Third, patient impact remains a central focus. By de-risking development and delivering reliable, scalable manufacturing capabilities, Abzena contributes to broader access to innovative therapies. While the company serves clients in the biopharma ecosystem, the ultimate objective is to bring effective treatments closer to patients who may benefit from them. This patient-centric orientation informs every aspect of Abzena’s program design, quality practices, and strategic investments in automation and data science.
From a customer perspective, the value proposition extends beyond speed and reliability. Clients gain access to a partner that can provide end-to-end continuity, enabling more coherent program narratives and more straightforward regulatory discussions. The data-centric culture also offers improved transparency, with clearer reporting on project status, risk assessments, and performance metrics. For sponsors, these capabilities translate into a more predictable development journey, better resource utilization, and stronger alignment with clinical and commercial targets.
In practice, the global facilities work in concert to manage the full spectrum of activities required for successful ADC and complex biologic programs. Early-stage discovery efforts in one location can be complemented by advanced analytics and conjugation chemistry expertise in another. Scale-up and GMP manufacturing can be executed with consistent quality controls, applying learnings across sites to optimize outcomes. This collaborative model strengthens Abzena’s ability to deliver on ambitious development timelines while maintaining stringent quality and regulatory compliance.
The broader implications for the biotech industry include a shift toward more integrated, technology-enabled CDMOs/CROs that can manage the entire lifecycle of biologics programs. As AI, automation, and data governance mature, companies like Abzena demonstrate how to translate scientific insight into scalable operations that satisfy regulatory standards and patient needs. The strategy highlights how a well-orchestrated mix of global capabilities, disciplined quality systems, and forward-looking digital infrastructure can unlock new possibilities in bioconjugate therapeutics and ADCs.
The client journey and program governance
For sponsors partnering with Abzena, the journey typically begins with a joint assessment of therapeutic targets, conjugation strategies, and development objectives. From there, the program is structured around integrated milestones, with cross-functional teams spanning chemistry, biology, analytics, manufacturing, and regulatory affairs. A central program governance framework ensures that the project remains on track, with regular reviews, risk registers, and data-driven decision points that guide subsequent steps.
As programs progress, data integration across the discovery, development, and manufacturing phases enables continuous learning. The analytics layer interprets experimental results, process data, and quality metrics to support go/no-go decisions and resource optimization. This data-centric approach helps clients understand the rationale behind each strategic choice, the anticipated outcomes, and the trade-offs involved in accelerating a particular development path. The end result is a more transparent, collaborative, and efficient partnership that aligns scientific ambition with practical execution.
In addition to program-specific benefits, Abzena’s global network supports business continuity and supply security. In a landscape characterized by supply chain volatility and regulatory scrutiny, the ability to manage materials, processes, and tooling across multiple sites reduces single-point risks. Clients gain confidence knowing that manufacturing and analytics capabilities are scalable and adaptable to changing demand, regulatory expectations, and emerging therapeutic modalities.
The patient-centric horizon and strategic implications
Abzena’s emphasis on patients in need underscores a broader industry trend toward patient-centric innovation. By prioritizing de-risked development pathways, reliable manufacturing, and accelerated timelines, Abzena contributes to reducing the time between scientific discovery and available therapies. This orientation resonates with the expectations of patients, clinicians, and healthcare systems seeking faster access to effective treatments while upholding safety and quality standards.
Strategically, Abzena’s model positions the company to leverage ongoing advances in AI, automation, and data science to sustain momentum across its programs. The modular services option also preserves the flexibility to tailor client engagements to changing priorities, enabling sponsors to shift resources toward high-impact activities as programs evolve. The commitment to global operations ensures that the company can respond to regional regulatory environments, clinical trial demands, and manufacturing needs without compromising consistency or quality.
From a market perspective, Abzena’s integrated, technology-enabled approach could influence how the industry structures partnerships for complex biologics and ADCs. As more organizations seek end-to-end solutions that can deliver speed, reliability, and regulatory alignment, CDMOs and CROs with strong data platforms and automation capabilities may become the preferred collaborators for ambitious biopharma programs. Abzena’s strategy reflects this shift by combining scientific depth with digital maturity and a patient-focused mission.
In the broader scientific ecosystem, Abzena’s emphasis on data-driven decision-making, rigorous cGMP compliance, and cross-site collaboration supports a culture of continuous improvement. This culture not only benefits individual programs but also contributes to industry-wide learnings about best practices in bioconjugation chemistry, ADC development, and the manufacturing of complex biologics. By sharing insights through internal research, industry collaborations, and knowledge exchange, Abzena can help raise the standard for quality, safety, and efficiency across the sector.
Conclusion
Abzena stands as a beacon of integrated biopharma development, merging end-to-end capabilities in bioconjugates, ADCs, and complex biologics with a robust data-driven strategy. The company’s global facilities—anchored by San Diego, Bristol, and Cambridge—enable seamless discovery, development, and manufacturing while maintaining stringent cGMP standards. Under the leadership of CIO Dave Williamson, Abzena emphasizes automation, AI, and a data-smart culture that accelerates outcomes and supports patient access to innovative therapies. By delivering fully integrated programs or tailored services, Abzena de-risks development and strengthens partners’ ability to navigate the path from laboratory insight to clinical success and commercial production. The convergence of scientific expertise, digital transformation, and patient-centric priorities positions Abzena to play a pivotal role in the evolving landscape of bioconjugates, ADCs, and complex biologics, driving meaningful advances for patients in need and advancing the capabilities of the global biopharma industry.