1. The interspecies scaling approach to predict clearance in humans from animal data was tested for a wide variety of drugs. 2. Three different methods were utilized to generate plots to scale-up the clearance values: (i) method I, clearance versus body weight (simple allometric equation); (ii) method II, product of clearance and maximum life-span potential; (iii) method III, product of clearance and brain weight versus body weight. 3. The circumstances under which the three methods can be applied to predict clearance in humans were evaluated. 4. If the exponent lies between 0.55 to 0.7 then method I predicts clearance reasonably well. 5. If the exponent lies between 0.71 to 1.0 clearance can be predicted reasonably well by method II. 6. If the exponent is > 1.0 clearance can be predicted using method III.

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It should be recognized that children are not small adults, hence dosing in children should not be a 'small adult dose'. A mean population dose in all age groups is just an average dose and not necessarily the best or the correct dose for a given patient. The dose of a drug varies from patient to patient and individual adjustment of the dose is always ideal but is not always practical. Theoretically, dose selection in paediatric drug development or clinical settings can be done by using either body weight or the clearance of a drug. Over the years, a lot of approaches have been suggested for the prediction of drug clearance or dose in paediatrics. Although some proposed methods are useful for the prediction of clearance or dose in children, there remains a high degree of uncertainty in the prediction of drug clearance or dose in children. In particular, the prediction of clearance or dose in an individual patient remains highly erratic. This review takes a critical look at these approaches and highlights the application and limitations of these proposed methods.

The objective of this study is to evaluate the predictive performance of several models to predict drug clearance in children ≤5 years of age. Six models (allometric model (data-dependent exponent), fixed exponent of 0.75 model, maturation model, body weight-dependent model, segmented allometric model, and age-dependent exponent model) were evaluated in this study. From the literature, the clearance values for six drugs from neonates to adults were obtained. External data were used to evaluate the predictive performance of these models in children ≤5 years of age. With the exception of a fixed exponent of 0.75, the mean predicted clearance in most of the age groups was within ≤50% prediction error. Individual clearance prediction was erratic by all models and cannot be used reliably to predict individual clearance. Maturation, body weight-dependent, and segmented allometric models to predict clearances of drugs in children ≤5 years of age are of limited practical value during drug development due to the lack of availability of data. Age-dependent exponent model can be used for the selection of first-in-children dose during drug development.

Tisagenlecleucel (Kymriah; Novartis Pharmaceuticals) is a CD19-directed genetically modified autologous T-cell immunotherapy. On August 30, 2017, the FDA approved tisagenlecleucel for treatment of patients up to 25 years of age with B-cell precursor acute lymphoblastic leukemia (ALL) that is refractory in second or later relapse. Approval was based on the complete remission (CR) rate, durability of CR, and minimal residual disease (MRD) <0.01% in a cohort of 63 children and young adults with relapsed or refractory ALL treated on a single-arm trial (CCTL019B2202). Treatment consisted of fludarabine and cyclophosphamide followed 2 to 14 days later by a single dose of tisagenlecleucel. The CR rate was 63% (95% confidence interval, 50%-75%), and all CRs had MRD <0.01%. With a median follow-up of 4.8 months, the median duration of response was not reached. Cytokine release syndrome (79%) and neurologic events (65%) were serious toxicities reported in the trial. With implementation of a Risk Evaluation and Mitigation Strategy, the benefit-risk profile was considered acceptable for this patient population with such resistant ALL. A study of safety with 15 years of follow-up is required as a condition of the approval. See related commentary by Geyer, p. 1133 Nonclinical Pharmacology and Toxicology Nonclinical safety studies were conducted with lentivirustransduced T cells prepared from healthy donors and patients in

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AimsIn recent years with the advent of paediatric exclusivity and requirements to conduct clinical studies in children, the current emphasis is to find a safe and efficacious dose of a drug in children. It has been suggested that one can predict the clearance of a drug in children according to the equation: CL in the child = adult CL × (weight of the child/70) 0.75 . Considering the controversy surrounding the exponent of 0.75 for the prediction of clearance and lack of any systematic evaluation of the aforementioned proposal, the objectives of the study were as follows: (i) to determine if indeed the exponent 0.75 is the most suitable exponent for the prediction of clearance in children from adult data; (ii) to explore and search for other exponents that are more accurate or as good as 0.75; and (iii) to propose a new approach (if any) based on the findings of the current evaluation. MethodsSix methods were used to predict clearance of drugs in children from adult data. Besides evaluating the exponent of 0.75, exponents of 0.80, 0.85 and 1.0 were also evaluated. An empirical approach based on kidney and liver weights was also examined. Based on the results of five methods, a sixth method was introduced. ResultsThe results of the study indicate that no single method is suitable for all drugs or for all age groups. The exponents 0.75, 0.80, and 0.85 provided the same degree of accuracy or error in the prediction of clearance in children. ConclusionsSince no single method is suitable for all drugs or for all age g roups. A combination of approaches is suggested which may help in improving the prediction of clearance in children from adult data.

The objective of this study was to evaluate the predictive performance of 4 allometric models to predict clearance in pediatric ages ranging from premature neonates to children ≤2 years of age. Four allometric models were used to predict clearances of 28 drugs in children from preterm neonates to 2 years of age (n = 564). The 4 models are (1) basal metabolic rate-dependent model; (2) age-dependent exponent model; (3) an allometric model based on kidney and liver weights as well as kidney and liver blood flow; and (4) an allometric model based on a fixed exponent of 0.75. The predictive performance of these models was evaluated by comparing the predicted clearance of the studied drugs with the observed clearance in an individual child. The results of the study indicated that the 3 new proposed models predicted the mean clearance of the drugs with reasonable accuracy (≤50% prediction error). On the other hand, the exponent of 0.75 produced substantial prediction error. Predicted individual clearance values were ≥50% in approximately 30% of the children by the proposed 3 methods and 73% by exponent 0.75. The 3 new proposed allometric models can predict mean clearances of drugs in children from premature neonates to ≤2 years of age with reasonable accuracy and are of practical value during pediatric drug development.