NICE Minutes 2014-11-14

From PHUSE Wiki
Jump to: navigation, search

Teleconference and computer link to Randy's desktop: 14 November 2014

Attendees: Alan, Paul, Carol, Philip, Lee, Randy

Agenda: Discussed progress made on pharmacologic class searching

Topics Discussed/Notes: Alan’s comments: queried the following publicly available databases: DailyMed, Drug Bank, FDA Drug Label Database, KEGG Drug (via Life Science Database Archive), and Drugs@FDA (NDA summaries) to see whether nonclinical and clinical safety data are available and associated with one-another. Thus far, my impression is that the greatest amount of clinical and nonclinical safety data are available via the FDA summary basis of approvals for NDA’s, although this information does not appear linked in a systematic fashion to pharmacologic class, and interconnectivity between clinical and nonclinical data is limited and not readily searchable. DailyMed was very helpful for locating drug labels via searches using generic drug name or pharmacologic class. The KEGG Drug database (from Japan) was very interesting and worth checking out, as it had very useful information that was readily obtained (other than toxicology).

Randy shared his desktop via a common link and gave a demonstration of the Pharmapendium (Elsevier; commercially available) software. Randy provided the following notes regarding Pharmapendium: Clinical and nonclinical data are available. Adverse effects/toxicities manually curated from FDA approval package docs (including Pharmacology Review), EMA approval docs, and post-marketing AERS reports and classified (e.g. using MEDRA); classified effects are linked to the primary document so that they can be viewed in context. Cannot easily identify class effects. Nonclinical and clinical adverse effects can be linked based on common terms (ontology). Term consistency issues: Can find cases where similar/identical effects have been mapped to different terms in the classification set (e.g., “Hepatic lesion”, Liver injury”); possible granularity differences when mapping detailed nonclinical pathology findings to more general MEDRA categories. Nonclinical-to-clinical term mismatching: nonclinical liver pathology findings mapping to same category as clinical liver injury findings. Species differences: not easy to identify adverse effects/toxicities that vary by nonclinical species (all species are lumped together into a single “Preclinical Data” category). Dose/ exposure-related comparisons cannot be made between clinical and nonclinical data. Also, pharmacologic class information can be found by “binning” or “grouping” similar compounds. Chemical structures can be searched, which will bring up approved drugs with shared substructures. Pharmapendium does not collect information from Medline. The currency of the data is not known.

Levels of data in Pharmapendium: 1) primary or source toxicology/human data, 2) summary data/content analysis created by FDA reviewers, 3) curated information prepared by software vendor (eg, Pharmapendium), 4) analysis level data obtained by end-user of software In the future, will SEND datasets make their way into search engines and software such as a Pharmapendium ?

Also discussed DailyMed and use of EPC = established pharmacologic class (FDA) and MoA = mechanism of action, developed by Veterans Administration NDF-RT. Should see Pharmacologic Class Mappings (SPL).

Key Decisions:

  1. Continue pharmacologic class searching, continue use of Pharmapendium
  2. The FDA Orange Book should be evaluated
  3. Team will work towards development of a search strategy guidance document/presentation

New Action Items:

  1. Alan will contact Elsevier to request temporary access to Pharmapendium for Philip