About:

PERK: An in-built application to predict and visualize environmental concentration and risk using pharmaceutical prescription data collected at fine spatial resolution.

PERK acronym for Predicting Environmental concentrations and RisK assessment, is an R package with in-built application tool, aims to facilitate automated modelling and reporting of predicted environmental concentrations of a comprehensive set of pharmaceuticals derived from a wide range of therapeutic classes with different mode of action.

The tool helps users,

  • to input their measured concentration,
  • to compare the predicted and measured concentrations of the APIs by means of the PEC/MEC ratio,
  • to establish whether the predicted equations used tend to underestimate or overestimate measured values.
  • It provides a consistent interactive user interface in a familiar dashboard layout, enabling users to visualise predicted values and compare with their measured values without any hassles.
  • Users can download data and graphs generated using the tool in .csv or publication ready images (.pdf, .eps).
  • Acknowledgments:

    This work is a part of the Wastewater Fingerprinting for Public Health Assessment (ENTRUST) project funded by Wessex Water and EPSRC IAA (grant no. EP/R51164X/1).


    Data sources:

    1. Prescription Data For England:

    This tool uses the prescription data from PrAna, an R package to calculate and visualize England NHS prescribing data.

    The data used in PrAna are as follows,

  • Prescribing data and Practice information are from the monthly files published by the NHS Business Service Authority, used under the terms of the Open Government Licence.
  • BNF codes and names are also from the NHS Business Service Authority's Information Portal, used under the terms of the Open Government Licence.
  • dm+d weekly release data is also from the NHS Business Service Authority's Information Portal, used under the terms of the Open Government Licence.
  • 2. WWTP Data:

    The following dataset are provided from WWTP collaborators,

  • Catchment map used to define the boundaries and capture the GP Practices inside the catchments for the prescription data calculations.
  • Daily flow data used to calculate the load and population equivalent.
  • Population Equivalent number of inhabitants per catchment zone.
  • Site information required to predict information such as recovery percentage.
  • Water quality parameters to predict population equivalent.
  • 3. API properties

  • Metabolites and Excretion factors collected from literatures and data repositories such as Drug bank.
  • Recovery percentage collected from literatures, calculated from measured concentration from previous experiments, predicted using WWTP site information.
  • Physio-chemical properties collected from literatures and data repositories.
  • Site information required to predict information such as recovery percentage.
  • Eco-toxicity data collected from literatures and data repositories.



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    Data Input


    Pharmaceuticals Data

    Environment Data (ENV)



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