Exploring the advantages and challenges of various clinical trial designs, including telescoped/seamless, N-of-1, exceptional responders, registry protocols, and real-world data, in the context of precision medicine and accelerated drug development.

Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular fea- tures that drive malignancies. Precision medicine has exploited next-generation sequencing and matched targeted therapy/immunotherapy deployment to successfully transform the outlook for several fatal cancers. Tumor and liquid biopsy genomic profiling and transcriptomic, immunomic, and proteomic interrogation can now all be leveraged to optimize therapy. Multiple new trial designs, including basket and umbrella trials, master platform trials, and N-of-1 patient-centric studies, are beginning to supplant standard phase I, II, and III protocols, allowing for accelerated drug evaluation and approval and molecular-based individualized treatment. Furthermore, real-world data, as well as exploitation of digital apps and structured observational registries, and the utilization of machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials have evolved, shifting from tumor type-centered to gene-directed and histology-agnostic trials, with innovative adaptive designs and personal- ized combination treatment strategies tailored to individual biomarker profiles. Some, but not all, novel trials now demonstrate that matched therapy correlates with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To further improve the precision medicine paradigm, the strategy of matching drugs to patients based on molecular features should be implemented earlier in the disease course, and cancers should have comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) tumor profiling. To overcome cancer complexity, moving from drug-centric to patient-centric individualized combination therapy is criti- cal. This review focuses on the design, advantages, limitations, and challenges of a spectrum of clinical trial designs in the era of precision oncology.

This paper identifies the need for rapid evidence appraisal to understand clinical uncertainties and inform both individual clinical decisions and public health messaging, while also highlighting the impact of chronic staff and bed shortages in the NHS on the delivery of life-saving care for diseases other than COVID-19.

We write this editorial some 2.5 years after the first national COVID-19 lockdown was announced in the UK on 17 March 2020. We reflect on the reality of how the pandemic and the national response to the pandemic affected a cancer care system that was already under severe strain.1 In their recent report on National Health Service (NHS) Cancer Services in April 2022, the House of Commons Health and Social Care Select Committee acknowledged gravely that the COVID-19 pandemic had a significant negative impact on cancer care, which is likely to result in a substantial loss of life-years.

This study highlights the challenges in implementing cancer screening programs, such as cultural and logistical barriers, low specificity of low-tech tests, and political interference, and emphasizes the need for detailed field assessment, improved IT infrastructure, and careful interpretation of mammography results to ensure a demonstrable reduction in mortality.

Cancer screening is a source of much debate. At the interface between public health, specialist care, economics and public health policy, it creates tensions between professional groups, politicians, the media and the public. A screening test may be cheap, but applying it to a population (with rigorous quality control and effective downstream processing of patients with abnormal results) creates a huge workload and cost. Screening can also have profound psychological effects. People with false-positive results require investigation yet are usually eventually found not to have cancer. Unless screening can be shown to reduce mortality from specific cancers, the resources used are better spent on improving care, and this has led to disparities in screening recommendations between countries. Advances in understanding the genetic basis of cancer are likely to provide new approaches to cancer risk assessment and new challenges for developing screening strategies, by risk-banding populations based on polymorphisms in low-penetrance cancer risk genes. The American Cancer Society guidelines for cancer screening, reviewed annually, represent a global gold standard that is difficult to emulate in most healthcare economies because of cost and under-capacity for downstream processing of abnormal findings. Tailoring cancer screening recommendations to a country's health economy is an essential public health intervention.

The DETECT-A study demonstrates that the positive predictive value (PPV) in cancer screening trials can be significantly improved by identifying high-risk patients, using multimarker testing, repetitive testing, excluding non-specific results, and incorporating sensitive radiological exams such as PET-CT.

Early detection is crucial for optimal treatment and prognosis of cancer. New approaches for pan-cancer screening comprise the comprehensive characterization of circulating tumor DNA (ctDNA) in plasma by next genera- tion sequencing and molecular profiling of mutations and methylation patterns, as well as fragmentation analysis. These promise the accurate detection and localization of multiple cancers in early disease stages. However, studies with real screening populations have to show their clinical utility and practicability.

This study found that radiomic features derived from planning CT can enhance the prediction of G1 late rectal toxicities, potentially guiding personalised treatment strategies and further research into the underlying biological mechanisms of toxicity.

This study aims to build machine learning models to predict radiation-induced rectal toxicities for three clinical endpoints and explore whether the inclusion of radiomic features cal- culated on radiotherapy planning computerised tomography (CT) scans combined with dosimetric fea- tures can enhance the prediction performance.

This study emphasizes the importance of clear communication in trial descriptions, the use of diagrams, and a staged consent process, along with the likelihood of multi-source funding in platform protocols for oncology trials.

Late‐phase platform protocols (including basket, umbrella, multi‐arm multi‐stage (MAMS), and master protocols) are generally agreed to be more efficient than traditional two‐arm clinical trial designs but are not exten‐ sively used. We have gathered the experience of running a number of successful platform protocols together to present some operational recommendations.