Tracks and Themes
Track 1: Applying Translational Principles Across the Development Lifecycle
Translational medicine aims to predict the benefit/risk profile of therapeutics during both clinical development programs and individualized patient care post-approval. As biotechnology drives innovation in novel modalities, new targets, and rare diseases, optimizing translational strategies becomes increasingly complex.
This track focuses on those approaches that span each development stage for all modalities, from more established ones such as monoclonal antibodies to newer ones such as cell and gene therapies. Distinct questions must be answered to enable successful progression at each stage of drug development. Leveraging current experience allows for the refinement of strategies across both established and emerging therapeutic platforms. Additionally, this track highlights strategies that drive progress from early discovery through preclinical studies, clinical trials, and, ultimately, to regulatory approval and market access by highlighting innovations, lessons learned, and best practices that enhance efficiency, reduce risk, and accelerate time to patients.
Theme 1: Bridging from Therapeutic Concept to First in Human
Keywords: Critical Quality Attributes (CQA), Artificial Intelligence (AI), Target Selection, Pharmacokinetic and Pharmacodynamic (PK/PD), Physiologically Based Pharmacokinetic (PBPK), Quantitative Systems Pharmacology (QSP), New Approach Methodologies (NAMs), Organoid, In Silico Models, In Vitro Models, Omics, First-In-Human (FIH), Regulatory Strategy.
In discovery and preclinical work, translational work is absolutely critical; the entire purpose of this stage is to develop in vitro and in vivo data sets that predict the safety and efficacy of a biotherapeutic in humans. The 3R principles of reduce, replace, and refine when it comes to animal studies have gained renewed attention as the FDA moves toward phasing out animal studies for monoclonal antibodies. This shift reflects significant scientific advancements over the past decade within in vitro and in silico tools, which not only offer viable alternatives to animal models but also enable more refined approaches where animal use remains necessary. This theme examines how these emerging technologies are being integrated into preclinical development to inform critical decisions such as target validation, dose selection, and safety assessments to ultimately support a more efficient and ethical transition from preclinical studies to first-in-human (FIH) trials. Emphasis is placed on maintaining scientific rigor while also leveraging innovative methods to improve translational success.
Topics in this theme include identifying clinically meaningful critical quality attributes, using artificial intelligence (AI) in formulation and manufacturing, evaluating the safety of new excipients and adjuvants, AI-informed and genetic-driven target selection, how to reach previously undruggable targets, modality selection matched to disease and target, organ-on-a-chip and organoid applications, advances in delivery vectors, delivering a drug to the site of action, clinical immunogenicity prediction, high-content sample analysis such as high resolution mass spectrometry (HRMS), microsampling to reduce sample size and animal numbers, new biomarker identification including omics approaches, reverse translation to validate preclinical models, pharmacokinetic and pharmacodynamic (PK/PD) models, physiologically based pharmacokinetic (PBPK) models, quantitative systems pharmacology (QSP) models, accelerating development for emerging infectious diseases, and bioanalytical challenges with complex biologics.
Theme 2: Bridging from First-in-Human to Registrational Trials
Keywords: Clinical Target Validation, Companion Biomarkers, Novel Vectors, Clinical Pharmacology, Proof of Concept, Benefit–Risk Assessment, Adaptive Trial Design.
In the early phases of clinical development, translational medicine plays a critical role in validating whether a drug has achieved the desired pharmacodynamic effect and whether that also results in the desired clinical outcomes, thereby clinically validating the mechanism of action. These studies are also essential for identifying the optimal dose and regimen to maximize the benefit–risk profile, rather than simply selecting the highest tolerable dose. Additionally, by uncovering covariates that may influence safety and efficacy, translational studies can inform the design of registrational trials, ensuring appropriate enrollment strategies and randomization to robustly evaluate these factors.
Topics in this theme include evaluation of novel vectors including viral and lipid nanoparticles, challenges accounting for variability in small data sets including Phase 1 and rare diseases, Phase 2, how to include women of child-bearing potential in trials, AI and machine learning in trial design, decentralized trial design and implementation, patient-centered data collection in clinical trials, selection of patient population likely to respond, clinical validation of targets and biomarkers, evaluating clinical risks from immunogenicity seroconversion, inferring gene expression data when tissue sampling not feasible, parallel testing of drugs and companion biomarkers, integrating data across multiple patient populations, building initial exposure/response models, developing composite biomarker to test in registrational trials, clinical pharmacology such as drug-drug interactions, risks of introducing fully human protein in patients with genetic mutation or knock-out, changes in peptide development after su
Theme 3: Bridging from Registrational Trials to Commercialization
Keywords: Companion Diagnostic, Commercial Formulation, Clinical Validation of Biomarker, Post-marketing, Precision Medicine, Prognostic Biomarkers, Patient Segmentation, Registration, Scalable Manufacturing.
Registrational trials build a robust database of information intended to support individualized patient risk-benefit assessments in commercial practice. By collecting comprehensive data and characterizing treatment responses, these trials enable further segmentation of the population based on key risk factors. This theme explores methodologies for analyzing these data and the evidentiary requirements needed to translate such insights into routine clinical decision-making.
Topics in this theme include evaluation of drug product changes and challenges between early development and scale-up to commercial process, intersection of microbiome and therapeutic effect, clinical validation of biomarkers including companion diagnostics, post-marketing surveillance, precision medicine, regulatory review of mechanistic data, requirements for biomarker inclusion in the label mechanism of action, validation of prognostic biomarkers and covariates that modulate response, genetic variant characterization, prediction of patient response to different medication options, expansion to new indications, registration with global health authorities beyond US and EMA, lessons learned from complete response letters, and recognizing successes in work involving novel modalities.
Track 2: Advancing Novel Medicine through Precision Science and Patient-Centric Innovation
Novel medicine refers to the development of therapies that significantly improve upon existing treatments or address unmet medical needs. This track focuses on the convergence of bioanalytics, computational tools, formulation design, manufacturing, and regulatory science to enable precise, scalable, and effective treatment for personalized care.
In addition, this track showcases innovations and best practices across discovery, development, and post-market refinement for novel therapies. Emphasis is placed on AI/ML integration, data mining, innovative technologies and approaches, evolving regulatory landscapes, novel formulation design, and adaptive manufacturing models for biologics and advanced therapeutic medicinal products (ATMPs). This track also highlights how pharmaceutical scientists are turning technologies and data into action, ensuring that the right treatment reaches the right patient at the right time with the right product.
Theme 1: Advancing Precision Therapeutics through AI Innovation and Global Regulatory Harmonization
Keywords: Innovative Medicine, Artificial intelligence (AI), Machine learning (ML), Federated Analytics, Real-World Evidence, Predictive & Real-Time Analytics, Regulatory Framework, ICH M10, FDA BMV, CLSI M70.
Artificial intelligence and machine learning are transforming drug development by turning big data (e.g., multi‑omics, real‑time manufacturing data), and clinical evidence into patient care, while regulators rapidly modernize guidance to keep pace. This theme explores how AI-driven analytics, digital tools, and harmonized regulatory frameworks shorten development timelines, enhance process robustness, and deliver high‑quality treatment in the era of personalized therapeutics.
Topics in this theme include AI/ML-driven workflow, disruptive technologies, and predictive modeling across drug development to enable acceleration and scalable personalized medicine. Regulatory insights include ICH M10, FDA biomarker/BMV guidance, CLSI M70, and IVDR-CLIA convergence, with adaptation of AI/ML to harness their benefits while mitigating the risks.
Theme 2: Advancing Precision Manufacturing and Delivery for Complex Modalities
Keywords: CMC, Formulation, Formulation Design, Drug Targeting, Advanced Therapy Medicinal Products (ATMPs), Lipid Nanoparticles (LNPs), Cell and Gene Therapies, Automation.
The manufacturing of personalized therapeutics presents unprecedented challenges in consistency, scalability, and quality control due to their complexity. This theme addresses how pharmaceutical scientists leverage integrated analytics, modular production, and harmonized reference standards to support complex therapy production.
Topics in this theme include advanced drug nanocarrier design, drug-targeted delivery and decentralized manufacturing, real-time bioanalytics, advanced excipient characterization. AI-enabled workflows to support rapid release testing and formulation adjustments, and how sustainable, resilient cold-chain systems ensure product integrity.
Theme 3: Advancing Cross-Modality Bioanalytics and Translational Biomarkers for Complex and Personalized Therapeutics
Keywords: Complex therapies, Pharmacokinetics and Pharmacodynamics (PK/PD), Immunogenicity, Complex Assays, Comparability, Innovation, Omics, Translational Biomarker, Modalities, Wearable & Real-World Data Collection.
Advanced biologics such as AAV gene therapies, cell therapies, T-cell engagers (TCEs), and multi‑mRNA LNPs demand both innovative bioanalytics and next‑generation biomarkers to optimize dosing, predict safety, and manage risks. This theme focuses on innovations that enable integration of PK/PD models, immunogenicity assessment and translational biomarkers to support adaptive trial designs and patient-tailored treatment regimens.
Topics in this theme include PK/PD, immunogenicity, and biomarker methodologies, complex assay development and characterization, and comparability strategies that span modalities. Early assessment of safety and efficacy are crucial for clinical development. Predictive modeling can be enabled via technologies such as multi‑omics, cfRNA, immune‑clonotype profiling, and high‑sensitivity off‑target editing panels. Wearable and real‑world data collection in addition to continuous physiologic monitoring aligned with clinical PK/PD and safety endpoints can refine personalized regimens. Global harmonization and regulatory alignment for effective immunogenicity assessments, assay comparability blueprints, and collaborative initiatives help accelerate global patient access.