Personalized Dosing of Infliximab in Patients With Inflammatory Bowel Disease Using a Bayesian Approach: A Next Step in Therapeutic Drug Monitoring

Although biological agents have revolutionized the management of inflammatory bowel diseases (IBDs), a significant proportion of patients show primary non-response or develop secondary loss of response. Therapeutic drug monitoring (TDM) is advocated to maintain the efficacy of biologic agents. Reactive TDM can rationalize the management of primary non-response and secondary loss of response and has shown to be more cost-effective compared with empiric dose escalation. Proactive TDM is shown to increase clinical remission and the durability of the response to a biologic agent. However, the efficacy of proactive and reactive TDM has been questioned in recent studies and meta-analyses. Hence, we need a different approach to TDM, which addresses inflammatory burden, the individual patient, and disease factors. Bayesian approaches, which use population pharmacokinetic models, enable clinicians to make better use of TDM for dose adjustment. With rapid improvement in computer technology, these Bayesian model-based software packages are now available for clinical use. Bayesian dashboard systems allow clinicians to apply model-based dosing to understand an individual's pharmacokinetics and achieve a target serum drug concentration. The model is updated using previously measured drug concentrations and relevant patient factors, such as body weight, C-reactive protein, and serum albumin concentration, to maintain effective drug concentrations in the serum. Initial studies have found utility for the Bayesian approach in induction and maintenance, in adult and pediatric patients, in clinical trials, and in real-life situations for patients with IBD treated with infliximab. This needs confirmation in larger studies. This article reviews the Bayesian approach to therapeutic drug monitoring in IBD

Molecular and structural analysis of metachromatic leukodystrophy patients in Indian population

Metachromatic leukodystrophy (MLD) is an autosomal recessive disorder caused by mutations in arylsulfatase A ( ARSA) gene. No work on molecular genetics of MLD has been reported from India and the mutational spectrum in Indian patients is not known. The present study was undertaken to identify mutations in arylsulfatase A gene in Indian MLD patients, to evaluate genotype–phenotype correlation, and to see the effect of the novel mutants on the protein. Twenty MLD patients (16 families) were screened by ARMS PCR for the most common mutation (c.459+1G>A). Pseudodeficiency alleles were tested by RFLP method whereas rare and novel mutations were scanned by Conformation Sensitive Gel Electrophoresis (CSGE), followed by sequencing. The genotype–phenotype correlation was also attempted. Protein homology modeling analysis was carried out for two novel missense mutations identified, to assess the effect of these mutations on the protein conformation. Nine pathogenic alleles were found in 13 patients (65%). Four previously reported mutations and five novel variants were identified. Five patients (35%) were found to have pseudodeficiency alleles, c.1049A>G (p.Asn350Ser) and c.1524+95A>G. Genotype–phenotype correlation was found to be difficult to establish. Protein modeling studies showed that the mutations cause loss of interactions leading to conformational change in ASA protein. The study identified the mutational spectrum of Indian MLD patients, which will be helpful in genetic counseling, carrier detection and establishing prenatal diagnosis. Homology modeling helped to study conformational change in protein and has implications in generating novel therapeutic molecules