Adverse Drug Reaction Profile of SGLT2 Inhibitor-Associated Diabetic Ketosis/Ketoacidosis in Singapore and their Precipitating Factors.

BACKGROUND AND OBJECTIVE: As of December 2017, 20 diabetic ketosis (DK)/diabetic ketoacidosis (DKA) cases associated with sodium-glucose co-transporter 2 inhibitors (SGLT2i) had been reported to the Health Sciences Authority (HSA), Singapore. We aimed to provide a detailed analysis of the profile of these cases. METHODS: As part of the emerging safety issue monitoring, the HSA followed up on SGLT2i-associated DK/DKA cases with the reporters to obtain the missing and/or supplementary information. Descriptive statistics were employed to summarise the data collected, while the Mann-Whitney test was employed to evaluate the differences between typical and euglycaemic DKA cases as well as between genders. RESULTS: All cases led to hospitalisation but were non-fatal. Where reported, the majority (71-85%) of DK/DKA cases occurred within 180 days of SGLT2i therapy initiation and involved female patients and/or patients with long-standing type 2 diabetes mellitus (T2DM). Apart from the difference in blood glucose levels, no differences in the profile between the typical and euglycaemic DKA cases were noted. Known precipitating factors were identified in all cases. Acute illnesses, particularly infections and abscesses, were the most commonly reported precipitating factors, followed by insulin dose reduction/cessation. CONCLUSIONS: Based on the profile of the reported cases, it is imperative to maintain clinical vigilance for DK/DKA, especially during the first 6 months of SGLT2i treatment and more so in female patients and/or patients with long-standing T2DM. Prompt evaluation and management of underlying precipitating factors is also important to assess and mitigate the risk of developing DK/DKA during treatment with SGLT2i.

Singapore Pharmacogenomics Portal: a web resource for evaluating human genetic variations of genes responsible for drug responses.

The Singapore Pharmacogenomics Portal is the first genomics web platform that links public resources from PharmGKB and DrugBank with population genetics data from the International HapMap Project and the Singapore Genome Variation Project. The web portal provides the opportunity to survey genetic differences across populations for all autosomal genes in the genome, and serves as an integrated platform for linking these data with drugs and genetic variants that affect drug responses, adverse reactions, and dosage requirements. We envisage that the information provided by the portal will be useful to drug regulators and clinical researchers when evaluating the transferability of results from clinical trials conducted in one population to other populations for which no direct clinical testing has been conducted. The utility of this resource may extend to other countries in the region that also have significant populations of Chinese, Malay, or Indian ancestry.

Pharmacogenetic risk for adverse reactions to irinotecan in the major ethnic populations of Singapore: regulatory evaluation by the health sciences authority.

BACKGROUND: For genetic polymorphisms known to alter drug effect or safety, regulatory authorities can tap into population genomic databases and other sources of allele and genotype distribution data to make a more informed decision about the anticipated impact of such variants on the main ethnic groups in a country's population. OBJECTIVE: The aim of this short communication is to describe how the Singapore Health Sciences Authority (HSA) made use of allele and genotype distributions in the main ethnic groups in Singapore (Chinese, Malay, Indian) and population genetic tools to compare with North American Caucasians and Japanese. METHODS: Published papers and publicly accessible genomic databases were searched up to August 2009 to obtain allele and genotype frequencies for UGT1A1*6 and *28, two common variants of UGT1A1, a gene that encodes for a key enzyme in the pathway of irinotecan metabolism. These variants are associated with greater risk of serious toxicity. RESULTS: In Singapore, the combined prevalence of three high-risk genotypes, UGT1A1*6/*6, *6/*28 and *28/*28, is 9.7% in Chinese, 5.0% in Malays and 18.7% in Indians, compared with 11.5% in North American Caucasians and 8.1% in Japanese. Indians are at an elevated risk of irinotecan-induced neutropenia associated with UGT1A1*28 compared with Chinese and Japanese, and at an even higher risk compared with North American Caucasians. On the other hand, Chinese and Japanese are at an elevated risk of irinotecan-induced neutropenia associated with UGT1A1*6 relative to Indians in Singapore or North American Caucasians. Population genotype data were the basis for the HSA to request revision of the package insert from manufacturers of irinotecan products. Moreover, the data provided the impetus for the HSA to publicize the availability of UGT1A1 genetic testing at the National Cancer Centre. CONCLUSION: With the growing volume of genomic data and pharmacogenomic associations, a regulatory authority is now able to more readily utilize population genetic information and tools to supplement evaluations of drug products pertinent to the country's ethnic demography.

Interethnic comparisons of important pharmacology genes using SNP databases: potential application to drug regulatory assessments.

BACKGROUND: The frequencies of alleles implicated in drug-response variability provide vital information for public health management. Differences in frequencies between genetically diverse groups of individuals can hamper drug assessments, particularly in populations where clinical data are not readily available. MATERIALS & METHODS: Making use of large, publicly available population genotype databases and population genetics tools, we developed a quick and efficient methodology to assess population divergence, which could be integrated into drug assessment and regulatory processes. To showcase its effectiveness, we present an analysis of population differences in a set of 42 important pharmacogenomics genes (PharmGKB) by utilizing allele frequencies of SNPs shared among three ethnic groups in the recently completed Singapore Genome Variation Project (Chinese, Malay and Indian) and four populations in the International HapMap project. RESULTS: The analyses facilitate comparisons across populations, such as identification of genes that exhibit moderate-to-high divergence between the main ethnic groups in Singapore and Caucasians, the dominant population in most drug-development programs. CONCLUSION: A potential use of the analyses is for regulators to develop a decision tree based on the extent of population divergence in key drug targets, metabolizing enzymes or transporter pathways when reviewing foreign clinical trial data. The methodology can be readily extended to other genes and countries with diverse ethnic groups. We continue to explore ways of integrating the information from these population genetics tools into stratifying the risk that the drug response established in one population could be translated to another.