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  1. Chow WL, Salleh NAM, Kang TS
    Ther Innov Regul Sci, 2024 May;58(3):528-538.
    PMID: 38376698 DOI: 10.1007/s43441-024-00620-x
    BACKGROUND: Drug approval lag is the time difference for new medicine to obtain marketing authorization approval in the study country compared to the first global approval. Drug approval lag delays the availability of innovative medicine to patients. This may lead to delay in treatment and severe public health implications. The study aimed to determine drug approval lag in Malaysia, the factors associated with drug approval lag (drug characteristics, regulatory factors and applicant type) and the association of the submission lag and review time with the regulation change.

    METHODS: All new pharmaceutical products approved between January 2015 and March 2021 were examined (n = 136) using publicly available information. Factors associated with drug approval lag were determined using multiple linear regression.

    RESULTS: The median drug approval lag was 855 days. Drug approval lag was associated with drug characteristics and regulatory factors. Median submission lag and median review time for products which fulfilled the requirement for the new regulations (Conditional Registration/ Facilitated Registration Pathway) were shorter compared to products which did not fulfil the requirement.

    CONCLUSION: Drug approval lag may delay the access of innovative medicine to patients, and this may lead to an increase in morbidity, mortality and healthcare costs. Good Regulatory Practices ensure efficient and transparent regulatory system which support the public health policy objectives in the most efficient way. The new regulations in Malaysia reduced the median submission lag and review time. The findings may be useful for regulators to consider for future policy development for medication access.

  2. Yong HS, Song SL, Lim PE, Chan KG, Chow WL, Eamsobhana P
    Sci Rep, 2015;5:15155.
    PMID: 26472633 DOI: 10.1038/srep15155
    The whole mitochondrial genome of the pest fruit fly Bactrocera arecae was obtained from next-generation sequencing of genomic DNA. It had a total length of 15,900 bp, consisting of 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region (A + T-rich control region). The control region (952 bp) was flanked by rrnS and trnI genes. The start codons included 6 ATG, 3 ATT and 1 each of ATA, ATC, GTG and TCG. Eight TAA, two TAG, one incomplete TA and two incomplete T stop codons were represented in the protein-coding genes. The cloverleaf structure for trnS1 lacked the D-loop, and that of trnN and trnF lacked the TΨC-loop. Molecular phylogeny based on 13 protein-coding genes was concordant with 37 mitochondrial genes, with B. arecae having closest genetic affinity to B. tryoni. The subgenus Bactrocera of Dacini tribe and the Dacinae subfamily (Dacini and Ceratitidini tribes) were monophyletic. The whole mitogenome of B. arecae will serve as a useful dataset for studying the genetics, systematics and phylogenetic relationships of the many species of Bactrocera genus in particular, and tephritid fruit flies in general.
  3. Yong HS, Song SL, Eamsobhana P, Goh SY, Lim PE, Chow WL, et al.
    PLoS One, 2015;10(7):e0134581.
    PMID: 26230642 DOI: 10.1371/journal.pone.0134581
    Angiostrongylus costaricensis is a zoonotic parasitic nematode that causes abdominal or intestinal angiostrongyliasis in humans. It is endemic to the Americas. Although the mitochondrial genome of the Brazil taxon has been published, there is no available mitochondrial genome data on the Costa Rica taxon. We report here the complete mitochondrial genome of the Costa Rica taxon and its genetic differentiation from the Brazil taxon. The whole mitochondrial genome was obtained from next-generation sequencing of genomic DNA. It had a total length of 13,652 bp, comprising 36 genes (12 protein-coding genes-PCGs, 2 rRNA and 22 tRNA genes) and a control region (A + T rich non-coding region). It is longer than that of the Brazil taxon (13,585 bp). The larger mitogenome size of the Costa Rica taxon is due to the size of the control region as the Brazil taxon has a shorter length (265 bp) than the Costa Rica taxon (318 bp). The size of 6 PCGs and the start codon for ATP6, CYTB and NAD5 genes are different between the Costa Rica and Brazil taxa. Additionally, the two taxa differ in the stop codon of 6 PCGs. Molecular phylogeny based on 12 PCGs was concordant with two rRNA, 22 tRNA and 36 mitochondrial genes. The two taxa have a genetic distance of p = 16.2% based on 12 PCGs, p = 15.3% based on 36 mitochondrial genes, p = 13.1% based on 2 rRNA genes and p = 10.7% based on 22 tRNA genes, indicating status of sibling species. The Costa Rica and Brazil taxa of A. costaricensis are proposed to be accorded specific status as members of a species complex.
  4. Lai NM, Leom DYX, Chow WL, Chen KH, Lin PH, Chaiyakunapruk N, et al.
    Neonatology, 2020;117(4):428-435.
    PMID: 32209794 DOI: 10.1159/000506703
    BACKGROUND: Research findings based on patient-important outcomes (PIOs) provide more useful conclusions than those that are based on surrogate outcomes. It is unclear to what extent PIOs are represented in neonatal randomized controlled trials (RCTs).

    OBJECTIVES: We determined the proportion of PIOs in neonatal RCTs included in Cochrane Neonatal reviews.

    METHODS: We extracted up to 5 outcomes from each RCT included in Cochrane Neonatal reviews published until January 2018, with independent determination of PIOs among authors followed by a discussion leading to a consensus. We defined PIOs as outcomes that matter to patient care, such as clinical events or physiological or laboratory parameters that are widely used to guide management.

    RESULTS: Among 6,832 outcomes extracted from 1,874 RCTs included in 276 reviews, 5,349 (78.3%) were considered PIOs; 461 studies (24.5%) included 5 or more PIOs, 1,278 (68.2%) included 1-4 PIOs, while 135 (7.2%) had no PIO included. PIOs were observed more often among dichotomous than among continuous outcomes (94.9 vs. 61.5%; RR: 1.54; 95% CI: 1.50-1.58), and more among subjective than among objective outcomes (95.9 vs. 76.8%; RR: 1.25; 95% CI: 1.22-1.28). Newer studies were more likely to have a greater number of PIOs (adjusted OR: 1.033 [95% CI: 1.025-1.041] with each publication year).

    CONCLUSIONS: The large and increasing representation of PIOs over the years suggests an improving awareness by neonatal trialists of the need to incorporate important outcomes in order to justify the utilization of resources. Further research should explore the reasons for non-inclusion or non-reporting of PIOs in a small proportion of RCTs.

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