Targeted Payloads in Oncology: What ADC Developers Can Learn from Radioligand Therapy

Introduction

Targeted payload delivery in oncology represents the use of potent cytotoxic agents or therapeutic molecules delivered directly to cancer cells, the ultimate aim being to maximize tumor death whilst minimising off-target effects. Oncology drug development is increasingly being defined by the precision of targeted payload delivery, rather than just target selection. While the first antibody-drug conjugate (ADC) was approved in the year 2000, early systemic radioisotope therapies were explored as early as the 1940s, establishing an early proof of concept for targeted radiation delivery that has since evolved into modern radioligand therapy (RLT). Both ADCs and RLT represent advanced, targeted drug delivery approaches in precision oncology, and important insights into in vivo payload distribution, off-target risks, and therapeutic index optimization can be learned by comparing their therapeutic development paradigms. This article will compare and contrast the design considerations for payload delivery in RLT versus ADCs, highlighting how imaging, dosimetry, and biodistribution studies in radiopharmaceuticals offer lessons for ADC pharmacology. These insights are increasingly relevant to Perceptive Discovery’s translational workflows, which utilize a wealth of experience to support the integration of quantitative imaging, biodistribution analysis, and pharmacokinetic modeling to improve early characterization of targeted payload behavior in oncology drug development.

ADC vs RLT

ADCs have emerged as a transformative pharmaceutical class of drugs designed to harness the specificity of antibodies with the potency of small-molecule therapeutics. ADCs are composed of an antibody linked to a targeted payload, or drug, designed specifically to discriminate between healthy tissue and diseased cells. ADCs were first combined with chemotherapy drugs, having since been explored in combination with other payloads such as immune-boosting agents, natural toxins, and even radioactive substances. RLT is an oncology treatment which couples a therapeutic radioactive isotope with a cancer-specific cell-targeting molecule known as the ligand, which, when bound to a cancer cell, releases radioactivity designed to selectively destroy it. Both ADCs and RLT are structurally aligned as modular targeted delivery systems and share common biological constraints. While they differ fundamentally in payload type, chemical vs radioactive, they share a common objective: to deliver potent and selective cytotoxic effects. As a result, lessons learnt across the two development programs may meaningfully enhance drug development and targeted payload delivery as a whole. RLT facilitates a more measurable relationship between biodistribution and biological effect, which can inform how ADC payload delivery can be quantified, optimized, and de-risked.

Top 5 Lessons from RLT for ADC Drug Development

1. Imaging-enabled biodistribution transforms translational confidence: RLT uses PET/SPECT imaging to directly visualize in vivo distribution, offering a level of spatial resolution that could significantly strengthen early ADC candidate selection and de-risk development decisions.
2. The therapeutic index should be defined by tissue exposure, not just dose: RLT relies on organ- and tumor-level absorbed dose (dosimetry), highlighting the value of moving ADC development toward exposure-based models rather than systemic dose escalation alone.
3. Early detection of off-target organ exposure improves safety prediction: RLT enables early identification of uptake in organs such as the liver and kidneys, providing a framework for anticipating ADC toxicity earlier in preclinical and translational studies.
4. Tumor heterogeneity in uptake must be explicitly accounted for: RLT demonstrates variable lesion-level uptake within and across patients, reinforcing the need for ADC strategies that consider spatial and inter-patient variability in target expression and delivery.
5. Integrated imaging–PK–PD modeling enhances predictability: RLT combines imaging-derived biodistribution with pharmacology and outcome data, suggesting a more integrated modeling approach could improve ADC translation from preclinical studies to clinical response.

Preclinical payload optimization to advance ADC development

From radiolabeling and biodistribution, to dosimetry and efficacy in diverse animal models, Perceptive Discovery delivers integrated, translatable data to accelerate your radiopharmaceutical pipeline from concept to clinic, utilizing lessons learned across both ADC and RLT drug development to accelerate translational success.

Our team of radiochemists, pharmacologists, cancer biologists, and imaging scientists brings deeply ingrained expertise across a broad spectrum of isotopes, modalities, and therapeutic platforms to enhance preclinical payload optimization. Whether developing a novel targeted radiotherapeutic or a companion diagnostic, we streamline radiolabeling, dosimetry, efficacy, and image analysis all under one roof.

Considered the leading preclinical radioligand therapy CRO, we provide end-to-end support for radiopharmaceutical development. With over 900+ preclinical RLT studies supported including 50+ IND-enabling dosimetry studies, we are a proven partner in bringing first-in-class radiopharmaceuticals to clinic.

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Resources

Ther Adv Med Oncol. Innovative payloads for ADCs in cancer treatment: moving beyond the selective delivery of chemotherapy. https://pmc.ncbi.nlm.nih.gov/articles/PMC11694294/

Nature. Antibody drug conjugate: the “biological missile” for targeted cancer therapy. https://www.nature.com/articles/s41392-022-00947-7

AAPS. Antibody Drug Conjugates: Design and Selection of Linker, Payload and Conjugation Chemistry. https://pmc.ncbi.nlm.nih.gov/articles/PMC4365093/

EORTC. Radioligand Therapy. https://www.eortc.org/scientific-strategy/radioligand-therapy-rlt/