Neurocognitive outcome and mental health in children with tyrosinemia type 1 and phenylketonuria: A comparison between two genetic disorders affecting the same metabolic pathway

Tyrosinemia type 1 (TT1) and phenylketonuria (PKU) are both inborn errors of phenylalanine–tyrosine metabolism. Neurocognitive and behavioral outcomes have always featured in PKU research but received less attention in TT1 research. This study aimed to investigate and compare neurocognitive, behavioral, and social outcomes of treated TT1 and PKU patients. We included 33 TT1 patients (mean age 11.24 years; 16 male), 31 PKU patients (mean age 10.84; 14 male), and 58 age- and gender-matched healthy controls (mean age 10.82 years; 29 male). IQ (Wechsler-subtests), executive functioning (the Behavioral Rating Inventory of Executive Functioning), mental health (the Achenbach-scales), and social functioning (the Social Skills Rating System) were assessed. Results of TT1 patients, PKU patients, and healthy controls were compared using Kruskal–Wallis tests with post-hoc Mann–Whitney U tests. TT1 patients showed a lower IQ and poorer executive functioning, mental health, and social functioning compared to healthy controls and PKU patients. PKU patients did not differ from healthy controls regarding these outcome measures. Relatively poor outcomes for TT1 patients were particularly evident for verbal IQ, BRIEF dimensions “working memory”, “plan and organize” and “monitor”, ASEBA dimensions “social problems” and “attention problems”, and for the SSRS “assertiveness” scale (all p values <0.001). To conclude, TT1 patients showed cognitive impairments on all domains studied, and appeared to be significantly more affected than PKU patients. More attention should be paid to investigating and monitoring neurocognitive outcome in TT1 and research should focus on explaining the underlying pathophysiological mechanism

Drug dosing during pregnancy—opportunities for physiologically based pharmacokinetic models

Drugs can have harmful effects on the embryo or the fetus at any point during pregnancy. Not all the damaging effects of intrauterine exposure to drugs are obvious at birth, some may only manifest later in life. Thus, drugs should be prescribed in pregnancy only if the expected benefit to the mother is thought to be greater than the risk to the fetus. Dosing of drugs during pregnancy is often empirically determined and based upon evidence from studies of non-pregnant subjects, which may lead to suboptimal dosing, particularly during the third trimester. This review collates examples of drugs with known recommendations for dose adjustment during pregnancy, in addition to providing an example of the potential use of PBPK models in dose adjustment recommendation during pregnancy within the context of drug-drug interactions. For many drugs, such as antidepressants and antiretroviral drugs, dose adjustment has been recommended based on pharmacokinetic studies demonstrating a reduction in drug concentrations. However, there is relatively limited (and sometimes inconsistent) information regarding the clinical impact of these pharmacokinetic changes during pregnancy and the effect of subsequent dose adjustments. Examples of using pregnancy PBPK models to predict feto-maternal drug exposures and their applications to facilitate and guide dose assessment throughout gestation are discussed

The status of pharmacometrics in pregnancy: highlights from the 3(rd) American conference on pharmacometrics.

Physiological changes during pregnancy may alter drug pharmacokinetics. Therefore, mechanistic understanding of these changes and, ultimately, clinical studies in pregnant women are necessary to determine if and how dosing regimens should be adjusted. Because of the typically limited number of patients who can be recruited in this patient group, efficient design and analysis of these studies is of special relevance. This paper is a summary of a conference session organized at the American Conference of Pharmacometrics in April 2011, around the topic of applying pharmacometric methodology to this important problem. The discussion included both design and analysis of clinical studies during pregnancy and in silico predictions. An overview of different pharmacometric methods relevant to this subject was given. The impact of pharmacometrics was illustrated using a range of case examples of studies around pregnancy

The status of pharmacometrics in pregnancy: highlights from the 3(rd) American conference on pharmacometrics.

Physiological changes during pregnancy may alter drug pharmacokinetics. Therefore, mechanistic understanding of these changes and, ultimately, clinical studies in pregnant women are necessary to determine if and how dosing regimens should be adjusted. Because of the typically limited number of patients who can be recruited in this patient group, efficient design and analysis of these studies is of special relevance. This paper is a summary of a conference session organized at the American Conference of Pharmacometrics in April 2011, around the topic of applying pharmacometric methodology to this important problem. The discussion included both design and analysis of clinical studies during pregnancy and in silico predictions. An overview of different pharmacometric methods relevant to this subject was given. The impact of pharmacometrics was illustrated using a range of case examples of studies around pregnancy

Evidence-based drug treatment for special patient populations through model-based approaches

The majority of marketed drugs remain understudied in some patient populations such as pregnant women, paediatrics, the obese, the critically-ill, and the elderly. As a consequence, currently used dosing regimens may not assure optimal efficacy or minimal toxicity in these patients. Given the vulnerability of some subpopulations and the challenges and costs of performing clinical studies in these populations, cutting-edge approaches are needed to effectively develop evidence-based and individualized drug dosing regimens. Five key issues are presented that are essential to support and expedite the development of drug dosing regimens in these populations using model-based approaches: 1) model development combined with proper validation procedures to extract as much valid information from available study data as possible, with limited burden to patients and costs; 2) integration of existing data and the use of prior pharmacological and physiological knowledge in study design and data analysis, to further develop knowledge and avoid unnecessary or unrealistic (large) studies in vulnerable populations; 3) clinical proof-of-principle in a prospective evaluation of a developed drug dosing regimen, to confirm that a newly proposed regimen indeed results in the desired outcomes in terms of drug concentrations, efficacy, and/or safety; 4) pharmacodynamics studies in addition to pharmacokinetics studies for drugs for which a difference in disease progression and/or in exposure-response relation is anticipated compared to the reference population; 5) additional efforts to implement developed dosing regimens in clinical practice once drug pharmacokinetics and pharmacodynamics have been characterized in special patient populations. The latter remains an important bottleneck, but this is essential to truly realize evidence-based and individualized drug dosing for special patient populations. As all tools required for this purpose are available, we have the moral and societal obligation to make safe and effective pharmacotherapy available for these patients too.status: publishe