Provides details such as Morphine Equivalent Dose (MED), 
    brand name and opioid content which are calculated of all oral opioids 
    authorized for sale by Health Canada and the FDA based on their Drug Identification Number (DIN) or National Drug Code (NDC). 
    MEDs are calculated based on recommendations by Canadian Institute for Health Information (CIHI) and Von Korff et al (2008)
    and information obtained from Health Canada's Drug Product Database's monthly data dump or FDA Daily database for Canadian and US databases respectively. 
    Please note in no way should output from this package be a substitute for medical advise.  
    All medications should only be consumed on prescription from a licensed healthcare provider.

Provides functions to analyze and visualize meristic and mensural
    phenotypic data in a comparative framework. The package implements an
    automated pipeline that summarizes traits, identifies diagnostic variables
    among groups, performs multivariate and univariate statistical analyses, and
    produces publication-ready graphics. Earlier implementation are
    described in Torres (2025) <doi:10.64898/2025.12.18.695244> (v1.0.0) 
    and Torres (2026) <doi:10.1002/ece3.73111> (v2.0.0).

Turn 'tidymodels' workflows into objects containing the
    sufficient sequential equations to perform predictions. These smaller
    objects allow for low dependency prediction locally or directly in
    databases.

A lightweight, fully vectorized N-body physics engine built for
    the R ecosystem. Simulate and visualize complex orbital mechanics,
    celestial trajectories, and gravitational interactions using tidy data
    principles. Features multiple numerical integration methods, including
    the energy-conserving velocity Verlet algorithm
    (Verlet (1967) <doi:10.1103/PhysRev.159.98>), to ensure highly stable
    orbital propagation. Gravitational N-body methods follow
    Aarseth (2003, ISBN:0-521-43272-3).

Seamlessly build and manipulate graph structures, leveraging
    its high-performance methods for filtering, joining, and mutating
    data. Ensures that mutations and changes to the graph are performed in
    place, streamlining your workflow for optimal productivity.