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Pharmacometrics and Systems Biology in Oncology: Is There an Intersection?

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Pharmacometrics and Systems Biology in Oncology: Is There an Intersection? International Journal of Clinical Pharmacology and Therapeutics, Vol. 51 – No. 1/2013 (89-90) Pharmacometrics and systems biology in oncology: Is there an intersection? Charlotte Kloft Extended Abstract Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie ©2013 Dustri-Verlag Dr. K. Feistle Universitaet Berlin, Berlin, Germany ISSN 0946-1965 DOI 10.5414/CPP51089 e-pub: December 21, 2012 Key words Background cine, mathematics and statistics: Pharmaco- pharmacometrics kinetic/pharmacodynamic/biomarker/disease – systems biology – Oncology involves a therapeutic area with monoclonal antibodies modeling aims to elucidate the mechanism- – biomarkers – systems complex and individual disease states and dis- based relationships between dosing – drug pharmacology ease progression and there is a limited num- exposure – resulting drug effects while incor- ber of anticancer drugs available. The drugs porating knowledge of the patients and their are usually administered in empirical com- disease [1]. plex dosing regimens which result in highly Systems biology aims from a bottom-up variable success rates. The following two ap- approach to model important system prop- proaches to achieve a more streamlined and erties to understand the complex pathways, rational drug development and drug treatment networks and regulatory and feedback mech- seem appealing: anisms on different spatial and temporal lev- 1. More sophisticated understanding of els [2]. the patient’s health/disease state and disease Due to their attractive characteristics (e.g. progression (“system”). high specificity to target, i.e., binding (only) 2. Development of new drugs with defined to specific disease-associated structures), and tailored treatment regimens. monoclonal antibodies (mAbs) present an The fundamental challenge of anticancer innovative class of biopharmaceuticals with drug treatment is to effectively eliminate can- increasing clinical importance. However, in cer cells in an individual patient using a treat- some cases only a certain fraction of patients ment protocol with dosing regimens that are benefits from these “targeted therapies” [3]. In tolerated. Most classical cytotoxic anticancer addition, in therapeutic use the outcome with agents do not distinguish between healthy and respect to efficacy and toxicity (incl. immuno- cancer cells and thus inhibit essential func- genicity) has been reported to be considerably tions in both healthy and malignant cell popu- variable suggesting mechanisms inherent to lations. A new generation of anticancer drugs patient (system) characteristics. has been designed to interfere with specific For two mAbs targeting the epidermal molecular targets identified as playing a criti- growth factor receptor (EGFR) system, cetux- cal role in tumor growth and progression. In imab and panitumumab, metastatic colorectal both cases, elucidation of the mechanisms and tumor patients bearing the mutated K-ras gene pathways at the molecular, cellular, tissue, or- did not benefit (progression-free and overall gan and organism level is crucial. There is an survival) from the drug treatment [4]. The urgent need for markers that indicate success, mAb trastuzumab has been approved in pa- failure or toxicity prior to or at an early stage tients with metastatic breast cancer but being of the anticancer treatment (“biomarkers”). indicated only in those ~ 25 – 30% of patients with relative overexpression of the HER2/neu Correspondence to receptor on the cell surface of the tumor cell. Prof. Dr. Charlotte Kloft Department of Clinical Methodology and concepts For these mAbs, the biomarkers K-ras and Pharmacy and Biochem- HER2 represent the status of the patient or the istry, Freie Universitaet Pharmacometrics represents an emerging state of disease. In their static use as ‘exclu- Berlin, Kelchstraße 31, science based on a transdisciplinary approach sion’ criterion, these biomarkers serve as a 12169 Berlin, Germany charlotte.kloft@ bridging concepts of biology, pharmacology, diagnostic tool and prevent useless or even fu-berlin.de clinical pharmacy and pharmacology, medi- harmful treatments for patients. In that, bio- Kloft 90 markers nowadays present an enormous value 2. key pathway markers in stratified (not personalized) medicine. 3. drug concentrations Additionally, the pharmacokinetics (PK) of 4. biomarker/PD data mAbs is unique compared to small molecule 5. pharmacogenetic data drugs: their binding/elimination characteristics comprise multiple pathways, in particular the 6. clinical data often observed parallel linear and nonlinear What is lacking today is not only the elimination pathways [5]. Furthermore, PK “network of experimental, in silico and clini- is also influenced by the pharmacodynam- cal data” but also the “network of method- ics (PD) and vice versa in terms of binding to ological expertise”. the target (“target-mediated drug disposition”, TMDD). Moreover, intracellular downstream In future, effective integration of both processes of the drug-receptor complex should disciplines – pharmacometrics and systems be taken into account [6]. Several PK and PD biology as systems pharmacology – might parameters have been reported to be related to not only foster research on pharmacokinet- patient demographic characteristics, e.g., the ics, pharmacodynamics and biomarkers for different clearances to body size [5]. However, disease and treatment outcome. Combining systematic and mechanistic investigations are approaches of cross-disciplinary interaction still sparse but highly warranted. (e.g. preclinical and clinical oncology) re- quiring open mindness and communication might also streamline decision making in the Perspectives two important fields: Both disciplines – pharmacometrics and (1) in drug development (known as: mod- systems biology – are rather young, have in- el-based drug development) and ternationally gained attractiveness but have up- (2) in patient care to increase the benefit/ to-now often been considered only separately. risk ratio of the therapeutic use in the indi- Especially in oncology, it is time to revisit the vidual tumor patient (proposed to be named current approaches of data generation and of as: model-based patient care). data analysis incl. modeling & simulation con- cepts. One objective in joint efforts could result in a thorough understanding of the underlying mechanisms of drug disposition, target bind- References ing, drug-target complex signal transduction, [1] Barrett JS, Fossler MJ, Cadieu KD, Gastonguay e.g. inside the cell in various sub-cellular com- MR. Pharmacometrics: a multidisciplinary field to partments and target dynamics, as well as the facilitate critical thinking in drug development and translational research settings. J Clin Pharma- impact of patient, treatment and study charac- col. 2008; 48: 632-649. teristics. To one end, biomarkers might extend doi:10.1177/0091270008315318 PubMed [2] Alberghina L, Westerhoff H. Systems Biology: their role from being used today in stratified Definitions and Perspectives. Topics in Current medicine based on target (non)expression to Genetics. 13. Berlin: Springer-Verlag, 2005. [3] Kuester K. Kloft C. Pharmacokinetics of mono- serving in future as mechanism-driven, predic- clonal antibodies In: B. Meibohm (Ed.), Wiley- tive biomarkers for personalized medicine. VCH Verlag, Weinheim, 2006; 45-91. [4] Karapetis CS, Khambata-Ford S, Jonker DJ, As a prerequisite, the strengths of basic O’Callaghan CJ, Tu D, Tebbutt NC, Simes RJ, and applied research groups have to be com- Chalchal H, Shapiro JD, Robitaille S, Price TJ, Shepherd L, Au HJ, Langer C, Moore MJ, Zalc- bined by exploiting the wealth of berg JR. K-ras mutations and benefit from cetux- imab in advanced colorectal cancer. N Engl J – Multiple levels of data, namely Med. 2008; 359: 1757-1765. doi:10.1056/NEJ- 1. molecular level Moa0804385 PubMed 2. cell level [5] Kuester K, Kovar A, Lüpfert C, Brockhaus B, Kloft C. Refinement of the population pharmaco- 3. tissue level kinetic model for the monoclonal antibody matu- zumab: external model evaluation and simula- 4. organ level tions. Clin Pharmacokinet. 2009; 48: 477-487. 5. patient level (→ society) doi:10.2165/11313400-000000000-00000 PubMed and [6] Krippendorff BF, Kuester K, Kloft C, Huisinga W. Nonlinear pharmacokinetics of therapeutic pro- – Multiple types of data (quantitative, over teins resulting from receptor mediated endocyto- time), namely sis. J Pharmacokinet Pharmacodyn. 2009; 36: 239-260. doi:10.1007/s10928-009-9120-1 1. target expression PubMed.
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