use("shiny")
use("bslib")
use("mrgsolve")
use("dplyr")
use("ggplot2")
use("tidyr")

# Pharmacokinetics and Pharmacodynamics of Glucarpidase Rescue Treatment
# after High-dose Methotrexate Therapy Based on Modeling and Simulation
# Kimura et al. Anticancer Research 43:1919-1924 (2023)

model_code <- '
$PARAM @annotated
CL_MTX      : 0.615 : Methotrexate clearance in delayed elimination setting (L/h)
VC_MTX      : 26.683 : Methotrexate central volume (L)
VP_MTX      : 2.253 : Methotrexate peripheral volume (L)
Q_MTX       : 0.078 : Methotrexate intercompartmental clearance (L/h)
CL_CPG2     : 0.310 : Glucarpidase clearance for 60 kg patient (L/h)
V_CPG2      : 4.114 : Glucarpidase volume for 60 kg patient (L)
KM_MTX      : 86 : Michaelis-Menten constant for MTX hydrolysis by CPG2 (umol/L)
ALPHA       : 1.20 : Catalytic capacity per glucarpidase activity concentration (umol/L/h per U/L)
WT          : 60 : Body weight (kg)
REF_WT      : 60 : Reference body weight (kg)

$CMT @annotated
MTX_CENT : Methotrexate central amount (umol)
MTX_PERI : Methotrexate peripheral amount (umol)
CPG2_CENT : Glucarpidase amount (U)

$MAIN
double CL_MTX_i = CL_MTX;
double VC_MTX_i = VC_MTX * (WT / REF_WT);
double VP_MTX_i = VP_MTX * (WT / REF_WT);
double Q_MTX_i = Q_MTX;
double CL_CPG2_i = CL_CPG2 * (WT / REF_WT);
double V_CPG2_i = V_CPG2 * (WT / REF_WT);

$ODE
double C_MTX = MTX_CENT / VC_MTX_i;
double C_CPG2_U_L = CPG2_CENT / V_CPG2_i;
double hydrolysis_umol_per_h = VC_MTX_i * ALPHA * C_CPG2_U_L * C_MTX / (KM_MTX + C_MTX);
if (hydrolysis_umol_per_h > MTX_CENT / 0.001) hydrolysis_umol_per_h = MTX_CENT / 0.001;

dxdt_MTX_CENT = -(CL_MTX_i / VC_MTX_i) * MTX_CENT -
  (Q_MTX_i / VC_MTX_i) * MTX_CENT +
  (Q_MTX_i / VP_MTX_i) * MTX_PERI - hydrolysis_umol_per_h;
dxdt_MTX_PERI = (Q_MTX_i / VC_MTX_i) * MTX_CENT - (Q_MTX_i / VP_MTX_i) * MTX_PERI;
dxdt_CPG2_CENT = -(CL_CPG2_i / V_CPG2_i) * CPG2_CENT;

$TABLE
double MTX_PLASMA = MTX_CENT / VC_MTX_i;
double MTX_PERIPHERAL = MTX_PERI / VP_MTX_i;
double CPG2_PLASMA = CPG2_CENT / V_CPG2_i;
double TARGET_01 = MTX_PLASMA <= 0.1;
double TARGET_1 = MTX_PLASMA <= 1.0;

$CAPTURE @annotated
MTX_PLASMA : Plasma methotrexate concentration (umol/L)
MTX_PERIPHERAL : Peripheral methotrexate concentration (umol/L)
CPG2_PLASMA : Plasma glucarpidase activity concentration (U/L)
TARGET_01 : Plasma MTX below 0.1 umol/L
TARGET_1 : Plasma MTX below 1.0 umol/L
'

mod <- mrgsolve::mcode("glucarpidase_mtx_mm", model_code)

mtx_mw_mg_per_umol <- 0.45444

simulate_glucarpidase <- function(mtx_g_m2 = 1, bsa = 1.73, infusion_h = 4,
                                  cpg2_dose_u_kg = 50, cpg2_time_h = 48,
                                  wt = 60, cl_fraction = 0.10,
                                  alpha = 1.20, end_h = 144, delta_h = 0.25) {
  mtx_mg <- mtx_g_m2 * 1000 * bsa
  mtx_umol <- mtx_mg / mtx_mw_mg_per_umol
  cpg2_units <- cpg2_dose_u_kg * wt

  dose_events <- data.frame(
    time = c(0, cpg2_time_h),
    amt = c(mtx_umol, cpg2_units),
    cmt = c(1, 3),
    evid = c(1, 1),
    rate = c(mtx_umol / infusion_h, 0)
  )

  mod |>
    mrgsolve::param(
      WT = wt,
      CL_MTX = 6.15 * cl_fraction,
      ALPHA = alpha
    ) |>
    mrgsolve::ev(dose_events) %>%
    mrgsolve::mrgsim(end = end_h, delta = delta_h) |>
    as.data.frame() |>
    dplyr::mutate(
      time_h = time,
      MTX_PLASMA = pmax(MTX_PLASMA, 0),
      MTX_PERIPHERAL = pmax(MTX_PERIPHERAL, 0),
      CPG2_PLASMA = pmax(CPG2_PLASMA, 0)
    )
}

metric_card <- function(output_id, label, class = "metric-primary") {
  div(class = paste("metric-card", class),
    div(class = "metric-value", textOutput(output_id)),
    div(class = "metric-label", label)
  )
}

app_theme <- bs_theme(
  version = 5,
  bootswatch = "flatly",
  primary = "#8b5cf6"
) |>
  bs_add_rules("
    .metric-card {
      background: #f8f9fa;
      border-radius: 8px;
      padding: 15px;
      margin: 5px;
      text-align: center;
      border: 1px solid #dee2e6;
    }
    .metric-value { font-size: 24px; font-weight: bold; color: #2c3e50; }
    .metric-label { font-size: 12px; color: #7f8c8d; }
    .metric-success .metric-value { color: #10b981; }
    .metric-warning .metric-value { color: #f59e0b; }
    .metric-primary .metric-value { color: #8b5cf6; }
    .metric-info .metric-value { color: #0dcaf0; }
    .ref-box {
      background: #f0f4ff;
      border-left: 4px solid #8b5cf6;
      padding: 12px 16px;
      border-radius: 4px;
      margin-top: 10px;
      font-size: 13px;
    }
    .ref-box a { color: #8b5cf6; }
    .small-note { color: #6c757d; font-size: 12px; }
  ")

ui <- page_sidebar(
  title = "Glucarpidase Rescue Simulator",
  theme = app_theme,
  sidebar = sidebar(
    title = "Simulation Settings",
    width = 340,
    accordion(
      open = c("Methotrexate", "Glucarpidase"),
      accordion_panel(
        "Methotrexate",
        numericInput("mtx_g_m2", "MTX dose (g/m²)", value = 1, min = 0.1, max = 12, step = 0.1),
        numericInput("bsa", "Body surface area (m²)", value = 1.73, min = 0.5, max = 2.5, step = 0.01),
        sliderInput("infusion_h", "MTX infusion duration (h)", min = 1, max = 24, value = 4, step = 1),
        sliderInput("cl_fraction", "MTX clearance fraction of normal", min = 0.02, max = 1, value = 0.10, step = 0.01)
      ),
      accordion_panel(
        "Glucarpidase",
        sliderInput("cpg2_dose", "Glucarpidase dose (U/kg)", min = 10, max = 80, value = 50, step = 10),
        sliderInput("cpg2_time", "Glucarpidase time after MTX start (h)", min = 4, max = 72, value = 48, step = 1),
        sliderInput("alpha", "Catalytic capacity scale", min = 0.05, max = 2.5, value = 1.20, step = 0.05)
      ),
      accordion_panel(
        "Patient and Display",
        sliderInput("wt", "Body weight (kg)", min = 10, max = 120, value = 60, step = 1),
        sliderInput("end_h", "Simulation duration (h)", min = 72, max = 240, value = 144, step = 12),
        checkboxInput("log_scale", "Log scale (Y-axis)", value = TRUE),
        checkboxInput("show_peripheral", "Show peripheral MTX", value = TRUE),
        checkboxInput("show_cpg2", "Show glucarpidase", value = TRUE)
      )
    )
  ),

  layout_column_wrap(
    width = 1/4,
    fill = FALSE,
    metric_card("mtx70", "MTX at 70 h (µmol/L)", "metric-success"),
    metric_card("mtx120", "MTX at 120 h (µmol/L)", "metric-warning"),
    metric_card("time_below_01", "First <0.1 µmol/L (h)", "metric-primary"),
    metric_card("cpg2_half", "Glucarpidase t½ (h)", "metric-info")
  ),

  card(
    card_header("Methotrexate Concentration-Time Profile"),
    full_screen = TRUE,
    plotOutput("pkPlot", height = "500px")
  ),

  navset_card_underline(
    title = "Model Information",
    nav_panel("Model Information", markdown("\
## Glucarpidase rescue after high-dose methotrexate

**Model structure:** Two-compartment methotrexate PK linked to one-compartment glucarpidase PK through a modified Michaelis-Menten hydrolysis term.

**Methotrexate parameters used for the default delayed-elimination scenario:** CL 0.615 L/h, Vc 26.683 L, Vp 2.253 L, Q 0.078 L/h. The default clearance fraction is 10% of normal, matching the simulation setting in the paper.

**Glucarpidase parameters:** CL 0.310 L/h and Vdss 4.114 L for a 60-kg patient, scaled linearly by weight. Default dose is 50 U/kg.

**Hydrolysis:** Km = 86 µmol/L. The catalytic scale is exposed because the paper reports the conversion constant indirectly from Vmax at 1 mol/L CPG2; the default is calibrated to the reported MTX <0.1 µmol/L at 70 h and rebound above 0.1 µmol/L at 120 h.

**Targets:** MTX <1.0 µmol/L is the clinically important reduction endpoint; MTX <0.1 µmol/L is the nontoxic threshold emphasized in the publication.
")),
    nav_panel("References", div(class = "ref-box",
      tags$h5("Key Reference"),
      tags$ol(
        tags$li("Kimura S, et al. Pharmacokinetics and Pharmacodynamics of Glucarpidase Rescue Treatment After High-dose Methotrexate Therapy Based on Modeling and Simulation. Anticancer Research. 2023;43:1919-1924."),
        tags$li("VORAXAZE (glucarpidase) prescribing information: recommended dose 50 U/kg IV for toxic plasma methotrexate concentrations with delayed elimination.")
      ),
      tags$h5("Therapeutic Context"),
      tags$ul(
        tags$li(tags$strong("Class:"), " Recombinant bacterial carboxypeptidase enzyme"),
        tags$li(tags$strong("Route:"), " Intravenous"),
        tags$li(tags$strong("Use:"), " Rescue treatment for delayed methotrexate elimination"),
        tags$li(tags$strong("Monitoring:"), " MTX rebound can occur; long-term monitoring beyond 144 h may be needed.")
      )
    ))
  ),

  div(style = "text-align: center; padding: 20px; margin-top: 30px;
      border-top: 1px solid #e9ecef; color: #6c757d; font-size: 12px;",
    "Powered by ",
    tags$a(href = "https://www.pkpdbuilder.com", target = "_blank",
           style = "color: #8b5cf6; font-weight: 500;", "PKPDBuilder.com"),
    " • Built by Sunny ☀️ (Husain Attarwala's AI Assistant)",
    br(),
    tags$span(style = "font-size: 10px;",
      "For research and educational purposes only. Not for clinical decision-making.")
  )
)

server <- function(input, output, session) {
  sim_data <- reactive({
    shiny::req(input$mtx_g_m2, input$bsa, input$cpg2_dose, input$wt)
    simulate_glucarpidase(
      mtx_g_m2 = input$mtx_g_m2,
      bsa = input$bsa,
      infusion_h = input$infusion_h,
      cpg2_dose_u_kg = input$cpg2_dose,
      cpg2_time_h = input$cpg2_time,
      wt = input$wt,
      cl_fraction = input$cl_fraction,
      alpha = input$alpha,
      end_h = input$end_h
    )
  })

  value_at_time <- function(data, target_h) {
    data$MTX_PLASMA[which.min(abs(data$time_h - target_h))]
  }

  output$mtx70 <- renderText({
    d <- sim_data()
    sprintf("%.3g", value_at_time(d, 70))
  })

  output$mtx120 <- renderText({
    d <- sim_data()
    sprintf("%.3g", value_at_time(d, 120))
  })

  output$time_below_01 <- renderText({
    d <- sim_data() |> dplyr::filter(time_h >= input$cpg2_time, MTX_PLASMA < 0.1)
    if (nrow(d) == 0) return("> end")
    sprintf("%.1f", min(d$time_h))
  })

  output$cpg2_half <- renderText({
    half_h <- log(2) / ((0.310 * input$wt / 60) / (4.114 * input$wt / 60))
    sprintf("%.1f", half_h)
  })

  output$pkPlot <- renderPlot({
    d <- sim_data()
    plot_data <- d |>
      dplyr::select(time_h, MTX_PLASMA, MTX_PERIPHERAL, CPG2_PLASMA) |>
      tidyr::pivot_longer(
        cols = c("MTX_PLASMA", "MTX_PERIPHERAL", "CPG2_PLASMA"),
        names_to = "Analyte",
        values_to = "Concentration"
      ) |>
      dplyr::mutate(
        Analyte = dplyr::recode(
          Analyte,
          MTX_PLASMA = "Plasma MTX (µmol/L)",
          MTX_PERIPHERAL = "Peripheral MTX (µmol/L)",
          CPG2_PLASMA = "Glucarpidase (U/L)"
        )
      )

    if (!input$show_peripheral) {
      plot_data <- plot_data |> dplyr::filter(Analyte != "Peripheral MTX (µmol/L)")
    }
    if (!input$show_cpg2) {
      plot_data <- plot_data |> dplyr::filter(Analyte != "Glucarpidase (U/L)")
    }
    if (input$log_scale) {
      plot_data <- plot_data |> dplyr::filter(Concentration > 0.001)
    }

    p <- ggplot(plot_data, aes(x = time_h, y = Concentration, color = Analyte)) +
      annotate("rect", xmin = -Inf, xmax = Inf, ymin = 0.1, ymax = 1.0,
               fill = "#10b981", alpha = 0.10) +
      geom_hline(yintercept = c(0.1, 1.0), linetype = "dashed", color = "#10b981", alpha = 0.7) +
      geom_vline(xintercept = input$cpg2_time, linetype = "dotted", color = "#8b5cf6", alpha = 0.8) +
      geom_line(linewidth = 0.9) +
      scale_color_manual(values = c(
        "Plasma MTX (µmol/L)" = "#111827",
        "Peripheral MTX (µmol/L)" = "#ef4444",
        "Glucarpidase (U/L)" = "#10b981"
      )) +
      labs(
        x = "Time after methotrexate start (h)",
        y = "Concentration",
        title = paste0("MTX ", input$mtx_g_m2, " g/m² over ", input$infusion_h,
                       " h + glucarpidase ", input$cpg2_dose, " U/kg at ", input$cpg2_time, " h"),
        subtitle = "Green band marks the 0.1–1.0 µmol/L monitoring range; dotted line marks glucarpidase administration",
        color = NULL
      ) +
      theme_minimal(base_size = 14) +
      theme(legend.position = "bottom")

    if (input$log_scale) {
      p <- p + scale_y_log10()
    }
    p
  })
}

shinyApp(ui = ui, server = server)