Cell and Gene Therapy: Transforming Treatment Paradigms for Patient-Centric Care.

Abbreviations

Chimeric antigen receptor T cell engineered T cells designed to recognize and eliminate targeted cells

cellular kinetics, referring to the pharmacokinetics of CAR T cells or gene‐modified cells in vivo

Model‐informed drug development, an approach that integrates quantitative models to support decision‐making in drug development

Quantitative systems pharmacology, which is a mechanistic analysis of dynamic interactions between drugs and biological systems, with the aim of understanding the behavior of the system as a whole and predicting drug‐system interactions quantitatively

Introduction

Cell and gene therapies (CGTs) represent a transformative advancement in modern medicine, offering not only the ability to treat but also the potential to cure certain diseases that were previously considered incurable. CGTs have made a paradigm shift in drug development, with rapid growth and evolving technologies [ 1 ]. As of August 2024, 46 CGTs have been approved by the FDA for 31 distinct indications [ 2 ]. Globally, by the first quarter of 2025, 104 CGTs have been approved and 3120 are in development, reflecting the accelerating momentum of this field [ 3 ].

Despite these advances in CGTs, several critical challenges remain, including appropriate dose optimization and limited data for long‐term efficacy and safety. These barriers underscore the need for robust translational and quantitative strategies to inform dose selection, mitigate toxicities, and optimize the benefit–risk balance, with tailored approaches for cell and gene therapy [ 4 , 5 ]. Quantitative tools such as quantitative systems pharmacology (QSP), exposure‐response modeling, and population pharmacokinetics are increasingly being strategized to support regulatory decision‐making and improve patient outcomes in CGT development [ 6 , 7 ].

A satellite conference of the ASCPT 2025 Annual Meeting on 4 April 2025, titled “Cell and Gene Therapy: Transforming Treatment Paradigms for Patient‐Centric Care,” offered a comprehensive examination of the current landscape and future directions of CGTs from scientific, clinical, and patient‐centered perspectives. The first half of the conference covered gene therapy's current status and future potential, lessons from approved gene therapies from clinical and patient perspectives, clinical pharmacology, and model‐informed drug development (MIDD) considerations. The second half of the conference shifted to T‐cell immunotherapies for oncology and autoimmune diseases, and the utility of MIDD approaches. Interactive panel discussions and Q&A segments throughout the conference with diverse stakeholders fostered a synthesis of key insights and emerging opportunities for advancing CGT through the lens of clinical pharmacology and translational science. This paper summarizes the key learnings from the half‐day conference.

Gene Therapy

Current Status and Future Perspective of Gene Therapy

Recent years have seen an explosion of CGTs across a range of diseases, with successful regulatory approvals worldwide, including bespoke therapies for single patients (i.e., n ‐of‐1 therapies) with ultra‐rare genetic diseases [ 8 , 9 , 10 ].

Gene therapies can be classified into those that deliver a payload of genetic material to the cell nucleus for expression, commonly referred to as “gene therapy,” and those that alter chromosomal DNA structure, referred to as “gene editing therapy” (Table 1 ). They are also divided into two subcategories by the mode of administration: in vivo, where a vector carrying gene‐modifying agents is administered directly to target tissues, and ex vivo, in which human cells are harvested, purified, transduced with a gene‐modifying agent outside of the body in a lab setting, and then readministered to the patient, sometimes with adjuvant therapy to facilitate engraftment. Most gene therapies to date are one‐time administration due to immunogenicity and high manufacturing costs. Crucially, unlike traditional small molecules or biologics, gene therapies show a disconnect between pharmacokinetic (PK) and pharmacodynamic (PD), making understanding their clinical pharmacology challenging. While PK profiles may be very short‐lived, sometimes merely hours or days, PD effects are ideally long‐lasting or permanent.

The complex and unique properties of gene therapies, including gene editing, pose commercial, manufacturing, and regulatory hurdles, requiring close collaboration between drug developers and regulators. Recent FDA CBER initiatives support “platformization” of gene therapies, allowing developers to leverage shared platform data (e.g., chemistry, manufacturing, and controls; toxicology and pharmacology) across multiple products using the same platform technology [ 12 ]. This approach can be applied to gene editing therapies tailored to different subtypes/mutations of a rare genetic disease or to gene delivery technologies targeting multiple distinct genes for separate diseases. By focusing regulatory review on product‐ and disease‐specific elements, it will shorten overall review timelines, ultimately streamlining gene therapy development.

With many unanswered questions remaining on the mechanistic, pharmacologic, safety, and durability profile of this advanced class of drugs, the near future for these products could herald a new era in the treatment of genetic diseases.

Lessons From Approved Gene Therapies for Hemophilia

Hemophilia A (HA) and Hemophilia B (HB) are rare X‐linked congenital bleeding disorders caused by mutations in the F8 or F9 genes that encode clotting factors VIII and IX, respectively. Disease severity correlates with factor activity levels, with severe hemophilia defined as less than 1% of normal activity. Spontaneous bleeds, particularly in joints and muscles, lead to chronic arthropathy, pain, and disability, and can be life‐threatening. Prophylactic treatment is recommended to prevent bleeds, and all current therapeutic options to date require lifelong adherence to repeat medication administration.

Three AAV‐based gene therapies for HA and HB have been approved by the FDA; however, fidanacogene elaparvovec for HB was recently withdrawn for commercial reasons [ 13 ]. Currently, two gene therapies are available: valoctocogene roxaparvovec for HA, and etranacogene dezaparvovec for HB.

Patient Perspectives

Hemophilia, once associated with significant morbidity, has seen transformative therapeutic advances, including extended half‐life factor products, nonfactor therapies (e.g., bispecific antibodies and rebalancing agents), and, most recently, gene therapies. Gene therapy offers the potential for a functional cure via a single infusion, yet uptake remains limited due to multiple interrelated factors—challenges that may have contributed to the recent market withdrawal of an approved gene therapy for HB [ 13 ].

Beyond structural barriers (such as institutional readiness, reimbursement complexity, and provider hesitancy), clinical and psychosocial considerations also play a role in limiting patient uptake of gene therapy. These include variable durability of factor expression, side effects (e.g., transaminitis), limited long‐term safety and efficacy data, and the “one‐and‐done” limitation of AAV‐based vectors. Post‐infusion lifestyle modifications (e.g., alcohol abstinence, barrier contraception, and intensive monitoring) and a mismatch between curative expectations and current outcomes further contribute to patient reluctance.

Shared decision‐making is especially critical in hemophilia, where treatments vary significantly in route, frequency, and risk–benefit profile. Personalized care must align not only with biological characteristics but also with patient‐defined values, goals, and preferences. In a recent single‐center survey of adults with severe hemophilia, 67% were satisfied with their current therapies, 65% had discussed gene therapy with a provider, and 6% were ready to pursue it immediately; 70% would consider it in the future, and 4% were not interested [ 14 ]. Common concerns included safety, efficacy, and cost, with many opting to remain on familiar, established treatments.

To better align research with patient priorities, investigators must directly address real‐world concerns and unmet needs. The National Bleeding Disorders Foundation (NBDF) has launched initiatives to embed lived experience experts (LEEs, individuals with bleeding disorders and their family members) into every stage of the research process, from protocol development to dissemination [ 15 , 16 ]. Their involvement has led to measurable improvements in trial design, recruitment, and inclusion criteria.

This perspective advocates for a cultural shift in biomedical research—one that democratizes knowledge production, center equity, and meaningfully engages patients to enhance the relevance, trustworthiness, and impact of emerging therapies.

Clinical Perspectives

For the HA gene therapy (valoctocogene roxaparvovec, ROCTAVIAN), the transgene is a B‐domain deleted, SQ form of F8 , reaching the maximum AAV packaging size. The HB gene therapy (etranacogene dezaparvovec, HEMGENIX) uses the Padua variant of F9 , which produces higher FIX activity than the wild‐type gene. Both are based on an AAV5 capsid, and the clinical dose is 6 × 10 13 vg/kg for the HA gene therapy, whereas it is 2 × 10 13 vg/kg for the HB gene therapy.

Data from valoctocogene roxaparvovec for HA showed an initial decline in FVIII activity, which was greatest over the first year, then decreased more slowly over time and began to stabilize around 3 years after transduction [ 17 ]. There was a sustained improvement in annualized bleeding rate (ABR) and improvement in quality of life as measured by Haemo‐QoL‐A scores. However, some participants returned to prophylactic treatment over time, correlated with declined FVIII levels. The most common adverse event was ALT elevation.

In contrast, data from etranacogene dezaparvovec for HB showed sustained FIX activity over time [ 18 ]. Participants with pre‐existing AAV5 antibodies were eligible, but they showed lower FIX expression than antibody‐negative participants. There was a sustained improvement in ABR, with 96% of participants remaining off prophylaxis until the last follow‐up, 2 years after transduction. The safety profile included common adverse events such as fatigue, headache, and arthralgia. ALT elevations were also observed but were less frequent than with the HA gene therapy although it should be noted that the criteria for defining ALT elevation were more stringent in the HA gene therapy program.

These data demonstrate that AAV gene therapy leads to clinically meaningful transgene expression in most patients despite significant interpatient variability in both HA and HB gene therapies, which is currently not fully explained. The mechanism underlying the declined FVIII expression over the first 1–3 years versus the stable FIX expression is a key unresolved question. ABR improvement was sustained over several years in both programs, even in patients with low transgene expression. The clinical significance of ALT elevations and the role of immunosuppression require further investigation. Finally, patients receiving gene therapy should be observed to further elucidate long‐term safety and efficacy.

Clinical Pharmacology Considerations for AAV ‐Based Gene Therapy

Clinical pharmacology aspects for AAV gene therapy center around its PK, PD, efficacy, and safety [ 6 ]. The PK of AAV gene therapy concerns its systemic biodistribution, inter‐ and intracellular trafficking and shedding of the viral capsid, and has been extensively studied in nonclinical species and from human biopsies. An emerging trend is to use physiologically based PK (PBPK) modeling to prospectively predict the biodistribution over time.

Transgene expressions are closely linked to PD, efficacy, and safety and can be characterized by the AAV dose–exposure–response relationship. QSP modeling has demonstrated promise in projecting the dose–exposure relationship informing clinical dose selection in conjunction with the widely used allometry‐based methods.

The durability of therapeutic response is paramount to clinical assessment and real‐world use. Durability should be interpreted as the cumulative magnitude of response accomplished over a specified period after dosing. The short‐term durability can be hampered by immune response against AAV, which may be ameliorated by prophylactic and/or on‐demand immunomodulatory (IM) or immunosuppressant (IS) regimen; a combination of IM/IS is increasingly used. The long‐term durability is linked to AAV genome stability, host cell turnover, and stress response to the transgene product.

Optimal IM/IS regimens and clinical dose selection informed by the totality of evidence will maximize the benefit‐to‐risk of AAV gene therapies. In addition, a deeper mechanistic understanding of immune response pathways, intrinsic/extrinsic factors that contribute to variability, and longitudinal PK/PD expression is required.

Challenges and Opportunities for MIDD in Gene Therapy Development

MIDD is a cross‐disciplinary framework developing quantitative models from preclinical and clinical data to inform decision‐making throughout the drug development process to improve trial efficiency, regulatory success, and dose optimization.

Clinical development of gene therapies has unique challenges, due to their one‐time dosing, complex mechanisms of action, and distinctive PK/PD properties such as biodistribution and shedding in place of traditional absorption, distribution, metabolism, and excretion (ADME) principles. As gene therapies usually target rare diseases, clinical development is further complicated by small, uncontrolled early studies, limited natural history data, and variability across programs in a highly competitive landscape. These factors create significant uncertainties in manufacturing, dose selection, trial design, and the benefit–risk assessment, which MIDD strategies should address.

However, traditional quantitative methods used for small‐molecule drugs are difficult to apply to gene therapies, mainly because PK‐PD model structures may not be directly applicable to these complex products. Even standard PK concepts (e.g., clearance) and the impact of intrinsic and extrinsic factors (e.g., body weight or co‐medications) are difficult to determine accurately with the uncertainty surrounding in vivo ADME concepts for gene therapies [ 19 ]. Nonetheless, the three pillars of key pharmacology concepts (exposure, expression, and modulation) remain applicable to gene therapy products [ 20 ] (Figure 1 ).

MIDD for gene therapies offers an opportunity where a comprehensive approach for integrating relevant data into quantitative models could greatly aid in the evaluation of safety and efficacy of these drugs (e.g., characterization of genetic subpopulations, seamless trial design, Bayesian borrowing approach to inform adverse event profiles in long‐term follow‐up studies).

T‐Cell Immunotherapy

Overview of T‐Cell Immunotherapy & Use of Biomarkers

T‐cell immunotherapies include tumor‐infiltrating lymphocytes (TIL) and genetically modified T cells such as chimeric antigen receptor T cells (CAR T) and T‐cell receptor‐engineered T cells (TCR T). To date, nine T‐cell immunotherapies have been approved by the FDA [ 2 ] (Table 2 ).

Clinical studies of CAR T therapies continue to identify product attributes and patient factors associated with efficacy and safety. The molecular and cellular attributes can affect their potency on a per‐cell basis and cellular kinetics (CK), subsequently affecting the efficacy and safety outcomes in patients. Adverse events highlighted include acute immune responses (i.e., cytokine release syndrome, immune effector cell–associated neurotoxicity syndrome), which can be fatal but are generally manageable with corticosteroids and IL‐6 or IL‐1 pathway blockade. Although some cases of secondary primary malignancies have been reported, the current consensus is that the therapeutic benefits of CAR T therapy outweigh the risks. Key parameters correlated with anti‐CD19 CAR T efficacy include low tumor burden, normal baseline inflammatory markers (e.g., IL‐6, CRP, and ferritin), and T‐cell attributes [ 21 ].

These clinical findings guide the preclinical development of next‐generation T‐cell therapies through refining in vitro, in vivo and in silico models. Advances in gene delivery and manufacturing technologies are accelerating the commercial viability of the next‐generation T‐cell therapies. Diverse T‐cell engineering strategies for CAR T are under investigation to increase efficacy, safety, and manufacturability (Table 3 ).

Allogeneic CAR T Therapy for Autoimmune Diseases

Emerging data show that anti‐CD19 CAR T can reset the B‐cell repertoire, alleviating B‐cell‐mediated autoimmune symptoms [ 22 ]. The factors that drive CK are similar between allogeneic and autologous CAR T cells, except that host immune rejection limits the persistence of allogeneic cells [ 23 ]. Unlike cancer, in autoimmune diseases, limited persistence may be sufficient for efficacy. Allogeneic CAR T thus holds appeal as an autoimmune therapy given its off‐the‐shelf availability, greater product standardization and control, and the potential for re‐dosing.

For autoimmune diseases, characterizing CAR T biodistribution and activity in non‐blood compartments (e.g., CNS, or other target organs) is critical to successful development, facilitating reverse translation to design more efficacious therapies. Nonetheless, identifying drivers of CK and activity in allogeneic CAR T remains challenging, considering high variability in CK with overlap across dose levels, cellular and humoral host immune rejection, and the impact of lymphodepletion. Strategies to mitigate graft rejection and reduce lymphodepletion burden are evolving. Modeling approaches may inform optimal lymphodepletion regimens. Oncology studies can inform other potential drivers of CAR T persistence.

Currently, clinical dose selection for allogeneic CAR T in autoimmune disease remains largely empirical, given the observed product‐ and patient‐related variability. Integrating a large amount of data using pharmacological modeling and machine learning models, as well as continuous cross‐functional collaboration is required to better understand key drivers of CK, efficacy, and safety.

MIDD for CAR T Therapy

CAR T cells exhibit unique CK that follow three sequential stages of exponential expansion, contraction, and long‐term persistence. Their complex and nonlinear biological responses make it challenging to interpret variability in nonclinical and clinical outcomes. A mechanistic modeling approach, such as a QSP model, can help predict safe and effective CAR T cell concentrations, provide insights into patient‐ and disease‐related factors and attributes of CAR T cells that drive the system dynamics governing the therapeutic response. Such models also aid in understanding biomarker responses and optimizing the design of next‐generation CAR T therapy.

As a case study, a mechanistic model was developed for an anti‐CD19 CAR T for B‐cell non‐Hodgkin lymphoma, based on Phase 1 clinical trial data [ 24 ]. The model integrated drug‐ and patient/disease‐specific variables, including CD4/CD8 cell ratios, tumor burden, and clinical outcome. It successfully captured individual patients' CK and PD such as B‐cell depletion. It demonstrated associations between CK, PD profiles, and clinical outcomes. Sensitivity analyses of key parameters (e.g., B‐cell division time, CD19 expression on B cells, binding affinity to CD19, and effector T‐cell killing capacity) indicated that both tumor characteristics and CAR T properties influence CK and PD profiles. For example, higher CD19 expression and stronger CAR affinity improved tumor cell killing, though responses varied across patient profiles.

Future MIDD applications include modeling other CAR‐engineered cell types, distribution to other tissues, toxicity mechanisms, and combination strategies with other therapies to enhance efficacy and safety.

Conclusion

CGTs are poised to redefine the future of medicine, offering the possibility of durable cures and reshaping the treatment paradigm across genetic, oncologic, and autoimmune diseases. Discussions at the ASCPT 2025 satellite conference emphasized that while today's challenges, including response, long‐term safety, cost, and patient acceptance, are significant, the trajectory of innovation is even more compelling. Advances in AAV gene therapy, lessons from hemophilia, and the expansion of CAR T therapies into autoimmune disease point to a future where curative intent is no longer rare but expected. Importantly, patient voices and translational experiences will increasingly guide research priorities, ensuring that therapies are not only scientifically sound but also aligned with patient values and equitable access. MIDD and next‐generation quantitative tools will accelerate translation, enabling more predictive, adaptive, and personalized approaches to CGT development. Looking forward, cross‐disciplinary collaboration among clinical pharmacology and translational scientists, clinicians, regulators, and patients will be crucial to unlocking CGTs' full potential. These collective efforts will catalyze a new era of health care, transforming CGTs from pioneering breakthroughs into standard, patient‐centric care worldwide.

Funding

The authors received no specific funding for this work.

Disclosure

Disclaimer : The contents of this presentation/publication and commentary are of the author(s) and do not represent the official views of the employer(s). Participation of S.Y. and T.M.R. in the CGT satellite conference and preparation of this manuscript were conducted in a personal capacity and are not affiliated with past or current employers. S.Y.'s contributions were made while she was an employee of the US FDA; she is currently employed by Alnylam.

Conflicts of Interest

S.Y. is an employee of Alnylam. A.M. is an employee of and holds stock in Pfizer Inc. T.M.R. is an employee of and holds stock in Takeda Development Center Americas Inc. M.Z.L. is an employee of Third Arc Bio and holds shares in Third Arc Bio. C.‐Y.W. and M.E.S. declared no conflicts of interest for this work.

Acknowledgments

The authors gratefully acknowledge Drs. Fyodor Urnov (Innovative Genomics Institute, UC Berkeley), Kefeng Sun (Vertex Pharmaceuticals), Dale Miles (Genentech), and John Burke (Reverb Therapeutics) for participating in the conference as speakers and sharing their expertise through presentations. While not all contributed directly to this manuscript, their insights and content were essential to the development of the conference summary.

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