Although anti-cancer treatments have significantly advanced over the past decades, obstacles to accomplishing successful treatment still exist. The occurrence of treatment resistance is one of the... Show moreAlthough anti-cancer treatments have significantly advanced over the past decades, obstacles to accomplishing successful treatment still exist. The occurrence of treatment resistance is one of the major factors that limit the long-lasting efficacy of anti-cancer treatment. Additionally, substantial variability in pharmacokinetics (PK) / pharmacodynamics (PD) of anti-cancer drugs also challenges successful oncology treatment. Therefore, gaining knowledge of and ultimately better suppressing evolutionary resistance development during treatment, and applying personalized treatment are desired to improve anti-cancer treatment. In this thesis, we have applied quantitative modeling approaches to address these needs, aiming for improved treatment for oncology patients. Our work demonstrated that with the quantitative models, the evolutionary progression of tumors could be characterized and predicted, accounting for interactions among heterogeneous tumor cells and supported by mutant gene variants detected in circulating tumor DNA (ctDNA). In addition, we developed population PK /PD models which enabled quantitative description of the PK and PD of anti-cancer drugs and corresponding variabilities in real-world patients. The developed models have been further applied to support the identification of optimal treatment strategies and guide individualized treatment for oncology patients. Show less
Classical statistical methods, such as p-values, are difficult for researchers to apply correctly. They for example do not allow drawing conclusions from a study early, or for extending a study... Show moreClassical statistical methods, such as p-values, are difficult for researchers to apply correctly. They for example do not allow drawing conclusions from a study early, or for extending a study with extra research groups that want to make their data available later. Sadly, in practice this often leads to faulty application of statistics and subsequent invalidity of experiment conclusions.Partly because of the above, recently, interest in safe, anytime-valid inference (SAVI) with e-values has emerged. This framework offers the same functionality as classical statistics, but also provides researchers with plenty of flexibility, for example through enabling early stopping and effect estimation at any time, extending a study in hindsight, and analyzing data located across multiple hospitals. In this thesis, this theory is further developed for performing SAVI in scenarios applicable to healthcare, specifically for several use-cases in psychiatry. It is explored how one could set up real-time psychiatry research in practice in an automated manner, combining text mining with network analysis techniques for data preparation and exploration and then confirming hypotheses with SAVI. Through this, the work in this thesis contributes to an environment where continuous learning from routinely collected healthcare data for better personalized recommendations is the new standard. Show less
In this thesis, different preclinical strategies were explored aiming at the identification of putative novel therapies for prostate and bladder cancer. The first part of this thesis (Chapter 2 and... Show moreIn this thesis, different preclinical strategies were explored aiming at the identification of putative novel therapies for prostate and bladder cancer. The first part of this thesis (Chapter 2 and Chapter 3) describes the generationof preclinical, patient-derived model systems of prostate and bladder cancer. In Chapter 2, an overview is provided of the most commonly used patient-derived model systems for urological tumors, and a framework on how these patient derived tumor models can be employed to address preclinical and clinical unmet needs is presented. In Chapter 3, we developed and optimized the culture of ex vivo tumor tissue slices and employed this model to detect anti-tumor responses of chemotherapeutic agents Docetaxel and Gemicitabin. Subsequently in Chapters 4, 5 and 6, we describe the use of multiple preclinical translational models, including patient-derived tumor models. In Chapter 4 and 5 the translational potential of the approved antipsychotic drug penfluridol was determined in bladder and prostate cancer. In Chapter 6, the use of oncolytic reovirus jin-3 as putative novel therapeutic strategy for the treatment of prostate is investigated. Finally, in Chapter 7, we describe a novel preclinical screening strategy based on E-cadherin (re)induction and inhibition of invasion for the identification of a new class of small molecules for the treatment of aggressive epithelial cancers. Show less
This thesis was aimed at optimizing immunosuppressive therapy in kidney transplant recipients using pharmacometric models. Kidney transplantation comprises the preferred treatment strategy for... Show moreThis thesis was aimed at optimizing immunosuppressive therapy in kidney transplant recipients using pharmacometric models. Kidney transplantation comprises the preferred treatment strategy for patients with end-stage kidney disease. Its clinical success is challenged by graft rejection, necessitating lifelong immunosuppressive therapy to accommodate host-graft adaptation. Herein, achievement of balanced immunosuppression is vital for optimal outcomes, but is complicated by pharmacokinetic variability of the immunosuppressants. Currently, therapeutic drug monitoring (TDM)-guided dose individualization is conducted in an effort to achieve immunosuppressant exposure with adequate rejection prophylaxis and minimal toxicity. However, TDM target attainment rates are low and graft rejection and toxicity are observed in patients with on-target immunosuppressant exposure, indicating a need for further improvement. Pharmacometrics harnesses options to modernize this endeavor, allowing for model-based prediction of individual pharmacokinetic behavior and dosage requirements from patient characteristics and pharmacokinetic observations. We reviewed the current state of pharmacometrics in kidney transplantation, developed pharmacometric models for alemtuzumab and iohexol, externally evaluated a model-based dosing tool for everolimus, and combined pharmacometrics with microsampling to enable remote monitoring of immunosuppressant exposure and kidney function, simultaneously. Our research underlines the broad applicability of pharmacometrics and provides an impulse for future research to further optimize immunosuppressive therapy in kidney transplantation. Show less
Flexible high-definition white-light endoscopy is the current gold standard in screening for cancer and its precursor lesions in the gastrointestinal tract. However, miss rates are high, especially... Show moreFlexible high-definition white-light endoscopy is the current gold standard in screening for cancer and its precursor lesions in the gastrointestinal tract. However, miss rates are high, especially in populations at high risk for developing gastrointestinal cancer (e.g., inflammatory bowel disease, Lynch syndrome, or Barrett's esophagus) where lesions tend to be flat and subtle. Fluorescence molecular endoscopy (FME) enables intraluminal visualization of (pre)malignant lesions based on specific biomolecular features rather than morphology by using fluorescently labeled molecular probes that bind to specific molecular targets. This strategy has the potential to serve as a valuable tool for the clinician to improve endoscopic lesion detection and real-time clinical decision-making. This narrative review presents an overview of recent advances in FME, focusing on probe development, techniques, and clinical evidence. Future perspectives will also be addressed, such as the use of FME in patient stratification for targeted therapies and potential alliances with artificial intelligence. Key Messages center dot Fluorescence molecular endoscopy is a relatively new technology that enables safe and real-time endoscopic lesion visualization based on specific molecular features rather than on morphology, thereby adding a layer of information to endoscopy, like in PET-CT imaging. center dot Recently the transition from preclinical to clinical studies has been made, with promising results regarding enhancing detection of flat and subtle lesions in the colon and esophagus. However, clinical evidence needs to be strengthened by larger patient studies with stratified study designs. center dot In the future fluorescence molecular endoscopy could serve as a valuable tool in clinical workflows to improve detection in high-risk populations like patients with Barrett's esophagus, Lynch syndrome, and inflammatory bowel syndrome, where flat and subtle lesions tend to be malignant up to five times more often. center dot Fluorescence molecular endoscopy has the potential to assess therapy responsiveness in vivo for targeted therapies, thereby playing a role in personalizing medicine. center dot To further reduce high miss rates due to human and technical factors, joint application of artificial intelligence and fluorescence molecular endoscopy are likely to generate added value. Show less
Tommel, J.; Evers, A.W.M.; Hamersvelt, H.W. van; Dijk, S. van; Chavannes, N.H.; Wirken, L.; ... ; Middendorp, H. van 2022
Background: Kidney failure and dialysis treatment have a large impact on a patient's life. Patients experience numerous, complex symptoms and usually have multiple comorbid conditions. Despite the... Show moreBackground: Kidney failure and dialysis treatment have a large impact on a patient's life. Patients experience numerous, complex symptoms and usually have multiple comorbid conditions. Despite the multitude of problems, patients often have priorities for improvement of specific aspects of their functioning, which would be helpful for clinicians to become informed of. This highlights a clear need for patient-centered care in this particular patient group, with routine screening as a vital element to timely recognize symptoms and tailored treatment to match individual patients' needs and priorities. By also providing feedback on patient's screening results to the patient itself, the patient is empowered to actively take control in one's mostly uncontrollable disease process. The current paper describes the study design of a multicenter randomized controlled trial evaluating the effectiveness of the "E-HEealth treatment in Long-term Dialysis" (E-HELD) intervention. This therapist-guided Internet-based cognitive-behavioral therapy (ICBT) intervention is focused on and personalized to the myriad of problems that dialysis patients experience and prioritize. Methods: After a screening procedure on adjustment problems, 130 eligible dialysis patients will be randomized to care as usual or the E-HELD intervention. Patients will complete questionnaires on distress (primary outcome measure), several domains of functioning (e.g., physical, psychological, social), potential predictors and mediators of treatment success, and the cost-effectiveness of the intervention, at baseline, 6-month follow-up, and 12-month follow-up. In addition, to take account of the personalized character of the intervention, the Personalized Priority and Progress Questionnaire (PPPQ) will be administered which is a personalized instrument to identify, prioritize, and monitor individual problems over time. Discussion: The present study design will provide insight in the effectiveness of tailored ICBT in patients with kidney failure who are treated with dialysis. When proven effective, the screening procedure and the subsequent ICBT intervention could be implemented in routine care to detect, support, and treat patients struggling with adjustment problems. Show less
Heuvel, L. van den; Meinders, M.J.; Post, B.; Bloem, B.R.; Stiggelbout, A.M. 2022
Background: The large variety in symptoms and treatment effects across different persons with Parkinson's disease (PD) warrants a personalized approach, ensuring that the best decision is made for... Show moreBackground: The large variety in symptoms and treatment effects across different persons with Parkinson's disease (PD) warrants a personalized approach, ensuring that the best decision is made for each individual. We aimed to further clarify this process of personalized decision-making, from the perspective of medical professionals. Methods: We audio-taped 52 consultations with PD patients and their neurologist or PD nurse-specialist, in 6 outpatient clinics. We focused coding of the transcripts on which decisions were made and on if and how decisions were personalized. We subsequently interviewed professionals to elaborate on how and why decisions were personalized, and which decisions would benefit most from a more personalized approach. Results: Most decisions were related to medication, referral or lifestyle. Professionals balanced clinical factors, including individual (disease-) characteristics, and non-clinical factors, including patients' preference, for each type of decision. These factors were often not explicitly discussed with the patient. Professionals experienced difficulties in personalizing decisions, mostly because evidence on the impact of characteristics of an individual patient on the outcome of the decision is unavailable. Categories of decisions for which professionals emphasized the importance of a more personalized perspective include choices not only for medication and advanced treatments, but also for referrals, lifestyle and diagnosis. Conclusions: Clinical decision-making is a complex process, influenced by many different factors that differ for each decision and for each individual. In daily practice, it proves difficult to tailor decisions to individual (disease-) characteristics, probably because sufficient evidence on the impact of these individual characteristics on outcomes is lacking. Show less
Neurodegenerative diseases, including Parkinson’s disease (PD), are increasing in prevalence due to the aging population. Despite extensive study, these diseases are still not fully understood and... Show moreNeurodegenerative diseases, including Parkinson’s disease (PD), are increasing in prevalence due to the aging population. Despite extensive study, these diseases are still not fully understood and the lack of personalised treatment options that can target the cause of the diseases, rather than the symptoms, has led to a greater demand for improved disease understanding, therapies and diagnostic procedures. In this thesis, we use systems biology approaches to construct disease-specific models intended for biomarker discovery, therapeutic treatment strategy identification and drug repurposing in PD. Systems biology is a mathematical field of research that analyses biological systems via construction of a computational model using experimental data. This is achieved by integration of omics data, including genomics, proteomics, transcriptomics and metabolomics. A specific approach used to identify the physico- and biochemical bounds within a biological system is constraint-based modelling, which requires the input of absolute quantitative metabolomics data. To improve our absolute quantitative coverage of the metabolome, we developed and improved new quantitative metabolomics methods using a targeted mass spectrometry workflow to obtain data intended to be integrated into constraint-based metabolic models for the study of PD. Show less
One of the main questions in Ewing sarcoma treatment is to identify low-risk patients that can be treated with less intensive treatment so that toxicity and the occurrence of long-term adverse... Show moreOne of the main questions in Ewing sarcoma treatment is to identify low-risk patients that can be treated with less intensive treatment so that toxicity and the occurrence of long-term adverse effects can be limited while still maintaining high cure rates or to identify those patients for whom treatment is expected to have limited benefit. Furthermore, to identify high-risk patients in which treatment needs to be intensified to improve outcome. Selection of risk groups and adjusted treatment allows for early decision making, will help to improve future outcomes and assists in clinical trial design. Additionally, treatment of Ewing sarcoma is multimodal and surgery, if feasible, is crucial for curative management. However, accurate detection and localization of tumor boundaries, especially in anatomical complex locations such as the pelvic is challenging. Inadequate surgical margins lead to a higher risk of local recurrence which has major impact on oncological outcome. Developments in intra-operative imaging, like CT-based navigation systems and near infrared (NIR)fluorescence guided surgery (FGS) make accurate defining and localization of surgical margins possible. They represent a whole new field of precision medicine and provide new treatment options for patients, thereby improving function outcome and healthcare quality. Show less
Klaveren, D. van; Balan, T.A.; Steyerberg, E.W.; Kent, D.M. 2019
Sunitinib treatment requires a personalized approach, since patients can respond very differently to this drug. Pharmacogenetics may improve our ability to provide a tailored therapy by studying... Show moreSunitinib treatment requires a personalized approach, since patients can respond very differently to this drug. Pharmacogenetics may improve our ability to provide a tailored therapy by studying how genetic variations could influence drug response. The objective of this thesis was to find genetic markers that can predict toxicity and efficacy of sunitinib in patients with metastatic renal cell carcinoma. This research builds upon previous findings from candidate gene studies by testing a selection of SNPs based on plausible involvement in pharmacokinetics or pharmacodynamics of the drug of interest. We observed that SNPs located in genes involved in metabolism and drug absorption (CYP3A4, CYP3A5, and ABCB1) are potentially associated with the clearance of sunitinib and its active metabolite. In analogy to this, we confirmed SNP associations from previous studies for SNPs in CYP3A5 and ABCB1 that predict the need for dose reductions and improvement of PFS on sunitinib. Sunitinib-induced toxicity is possibly related to SNPs in CYP3A4 and CYP3A5, and in interleukin genes IL8 and IL13. VEGFR-2 (KDR) rs34231037 G-allele variant carriers were potentially associated with a favorable response to sunitinib. A GWAS learned us that SNPs in chromosome 21 are involved in sunitinib efficacy, probably by influencing drug resistance mechanisms. Show less
