library(shiny)
library(bslib)
library(mrgsolve)
library(dplyr)
library(ggplot2)

# ---------------------------------------------------------------------------
# mrgsolve 1-compartment model for Dolutegravir (DTG)
# Pop PK parameters: Dooley et al. (2015) Br J Clin Pharmacol
# CL/F = 0.901 L/h, V/F = 17.4 L, Ka = 2.24 h-1, tlag = 0.263 h
# Allometric scaling; pregnancy & DDI modifiers on CL
# ---------------------------------------------------------------------------
model_code <- '
$PARAM @annotated
CL    : 0.901  : Apparent oral clearance (L/h)
V     : 17.4   : Apparent volume of distribution (L)
KA    : 2.24   : Absorption rate constant (1/h)
ALAG  : 0.263  : Absorption lag time (h)
WT    : 70     : Body weight (kg)
PREGF : 1.0    : Pregnancy CL multiplier (1.0=none, 1.72=2nd tri, 1.85=3rd tri)
DDIF  : 1.0    : Drug-interaction CL multiplier

$CMT @annotated
DEPOT : Oral depot compartment (mg)
CENT  : Central compartment (mg)

$MAIN
double CLi = CL * pow(WT / 70.0, 0.75) * PREGF * DDIF;
double Vi  = V  * (WT / 70.0);
ALAG_DEPOT = ALAG;
F_DEPOT    = 1.0;

$ODE
dxdt_DEPOT = -KA * DEPOT;
dxdt_CENT  = KA * DEPOT - (CLi / Vi) * CENT;

$TABLE
double CP = CENT / Vi;   // mg/L = µg/mL

$CAPTURE CP
'

mod <- mcode("dolutegravir", model_code)

# ---------------------------------------------------------------------------
# Theme
# ---------------------------------------------------------------------------
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; }
")

# ---------------------------------------------------------------------------
# UI
# ---------------------------------------------------------------------------
ui <- page_sidebar(
  title = "Dolutegravir (DTG) PK Simulator",
  theme = app_theme,

  sidebar = sidebar(
    title = "Simulation Settings", width = 340,

    h6("Dosing"),
    sliderInput("dose", "Dose (mg)", min = 25, max = 100, value = 50, step = 25),
    radioButtons("interval", "Dosing Interval",
      choices  = list("Once Daily (Q24H)" = "24", "Twice Daily (Q12H)" = "12"),
      selected = "24"),
    numericInput("n_days", "Duration (days)", value = 14, min = 1, max = 28),

    hr(), h6("Patient Characteristics"),
    sliderInput("wt", "Weight (kg)", min = 40, max = 120, value = 70, step = 5),
    selectInput("pregnancy", "Pregnancy Status",
      choices = list(
        "Non-Pregnant"           = "none",
        "2nd Trimester (~24 wks)" = "t2",
        "3rd Trimester (~33 wks)" = "t3"
      ), selected = "none"),

    hr(), h6("Drug-Drug Interactions"),
    selectInput("ddi", "Co-medication",
      choices = list(
        "None (no inducer)"            = "1.0",
        "Rifampin (strong inducer)"    = "2.3",
        "Efavirenz / Nevirapine"       = "1.25",
        "Carbamazepine / Phenytoin"    = "2.0"
      ), selected = "1.0"),

    hr(),
    checkboxInput("log_scale", "Log Scale (Y-axis)", value = FALSE)
  ),

  navset_card_underline(
    title = "Dolutegravir PK Simulator",
    full_screen = TRUE,

    nav_panel("Simulation",
      layout_column_wrap(width = 1/4, fill = FALSE,
        div(class = "metric-card metric-success",
          div(class = "metric-value", textOutput("cmax")),
          div(class = "metric-label", "Cmax,ss (µg/mL)")),
        div(class = "metric-card metric-warning",
          div(class = "metric-value", textOutput("ctrough")),
          div(class = "metric-label", "Ctrough / C24h (µg/mL)")),
        div(class = "metric-card metric-primary",
          div(class = "metric-value", textOutput("auc")),
          div(class = "metric-label", "AUCtau,ss (µg·h/mL)")),
        div(class = "metric-card metric-info",
          div(class = "metric-value", textOutput("thalf")),
          div(class = "metric-label", "t½ (h)"))
      ),
      card(full_screen = TRUE,
        plotOutput("pkPlot", height = "500px")
      )
    ),

    nav_panel("Model Information",
      markdown("
## Dolutegravir (DTG) — 1-Compartment Oral PK Model

**Drug:** Dolutegravir (DTG; Tivicay®) — HIV Integrase Strand Transfer Inhibitor (INSTI)
**Indication:** HIV-1 infection in adults and adolescents ≥12 years

**Model structure:** 1-compartment, first-order absorption with lag time, first-order elimination

### Population PK Parameters

| Parameter | Estimate | Units | Source |
|-----------|----------|-------|--------|
| CL/F      | 0.901    | L/h   | Dooley et al. 2015 |
| V/F       | 17.4     | L     | Dooley et al. 2015 |
| Ka        | 2.24     | h⁻¹   | Dooley et al. 2015 |
| t_lag     | 0.263    | h     | Dooley et al. 2015 |
| t½        | ~14      | h     | FDA label          |

### Allometric Scaling
- **CL:** CL/F × (WT/70)^0.75 × PREGF × DDIF
- **V:** V/F × (WT/70)

### Protein Binding
- Highly protein bound: **≥98.9%** (fu = 0.007)
- Albumin levels decrease during pregnancy → fraction unbound increases (0.007 → 0.0084 in 2nd, 0.0088 in 3rd trimester)

### Pregnancy Effects (Liu et al. 2020, PBPK Model)
Enzyme induction increases total clearance:
- **2nd trimester:** UGT1A1 ×1.75 + CYP3A4 ×1.60 → CL ↑ ~72% (PREGF = 1.72)
- **3rd trimester:** UGT1A1 ×1.92 + CYP3A4 ×1.60 → CL ↑ ~85% (PREGF = 1.85)
- Standard 50 mg QD dose is generally maintained; therapeutic drug monitoring recommended

### Drug-Drug Interactions
| Co-medication | Effect on CL | AUC Change | Recommendation |
|--------------|-------------|------------|----------------|
| Rifampin | ×2.3 | ↓ ~54% | Adjust to 50 mg BID |
| Efavirenz/Nevirapine | ×1.25 | ↓ ~20% | 50 mg BID if INSTI-naive |
| Carbamazepine | ×2.0 | ↓ ~49% | Avoid or adjust dose |

### Therapeutic Target
- IC90-PA (protein-adjusted): **0.064 µg/mL** — shown as dashed red line
- Recommended minimum Ctrough > 0.064 µg/mL for viral suppression
- Standard dosing maintains trough typically **>1 µg/mL** (>>IC90)

### Metabolism
- **UGT1A1:** ~79% of dose (primary)
- **CYP3A4:** ~21% of dose
- Renal excretion: <1% unchanged
      ")
    ),

    nav_panel("References",
      div(class = "ref-box",
        tags$h5("📚 Key References"),
        tags$ol(
          tags$li("Liu XQ et al. (2020) Clin Pharmacokinet 59:781-797 — PBPK modeling of DTG and RAL in pregnancy (source paper)"),
          tags$li("Dooley KE et al. (2015) Br J Clin Pharmacol 80(5):1085-96 — Population PK of dolutegravir in HIV treatment-naive patients"),
          tags$li("Tivicay® (dolutegravir) FDA Prescribing Information (2023) — FDA.gov"),
          tags$li("DHHS Panel on Antiretroviral Guidelines (2024) — Recommendations for ARV therapy in adults/adolescents with HIV"),
          tags$li("Zamek-Gliszczynski MJ et al. (2018) Clin Pharmacol Ther 103:916-925 — DTG and neural tube defects, folate receptor")
        ),
        tags$h5("💊 Drug Summary"),
        tags$ul(
          tags$li(tags$strong("Class:"), " HIV Integrase Strand Transfer Inhibitor (INSTI)"),
          tags$li(tags$strong("Brand:"), " Tivicay® (ViiV Healthcare)"),
          tags$li(tags$strong("Standard dose:"), " 50 mg once daily (treatment-naive/experienced, resistance-free)"),
          tags$li(tags$strong("Alternative dose:"), " 50 mg twice daily (with certain inducers or INSTI resistance)"),
          tags$li(tags$strong("Metabolism:"), " UGT1A1 (~79%), CYP3A4 (~21%); substrate of P-gp and BCRP"),
          tags$li(tags$strong("Protein binding:"), " ≥98.9%"),
          tags$li(tags$strong("Half-life:"), " ~14 hours"),
          tags$li(tags$strong("Pregnancy:"), " Recommended in 2nd/3rd trimester; avoid peri-conception (neural tube risk)")
        )
      )
    )
  ),

  div(
    style = "text-align: center; padding: 20px; margin-top: 30px; border-top: 1px solid #e9ecef; color: #6c757d; font-size: 12px;",
    "Powered by ",
    tags$a(href = "https://www.pkpdbuilder.com", target = "_blank",
           style = "color: #8b5cf6; font-weight: 500;", "PKPDBuilder.com"),
    " • Simulated with mrgsolve | Liu et al. 2020 & Dooley et al. 2015", br(),
    tags$span(style = "font-size: 10px;",
      "For research and educational purposes only. Not for clinical decision-making.")
  )
)

# ---------------------------------------------------------------------------
# Server
# ---------------------------------------------------------------------------
server <- function(input, output, session) {
  # thematic::thematic_shiny()

  preg_factor <- reactive({
    switch(input$pregnancy,
      "none" = 1.0,
      "t2"   = 1.72,
      "t3"   = 1.85,
      1.0
    )
  })

  sim_data <- reactive({
    shiny::req(input$dose, input$wt, input$n_days)
    interval <- as.numeric(input$interval)
    n_doses  <- ceiling(as.numeric(input$n_days) * 24 / interval)
    ev1 <- ev(amt = input$dose, cmt = 1, ii = interval, addl = n_doses - 1)
    mod |>
      param(WT = input$wt, PREGF = preg_factor(), DDIF = as.numeric(input$ddi)) |>
      ev(ev1) |>
      mrgsim(end = as.numeric(input$n_days) * 24, delta = 0.25) |>
      as.data.frame() |>
      dplyr::mutate(time_h = time)
  })

  output$cmax <- renderText({
    d    <- sim_data()
    last <- d |> dplyr::filter(time >= (as.numeric(input$n_days) - 1) * 24)
    sprintf("%.2f", max(last$CP, na.rm = TRUE))
  })

  output$ctrough <- renderText({
    d    <- sim_data()
    last <- d |> dplyr::filter(time >= (as.numeric(input$n_days) - 1) * 24)
    sprintf("%.2f", min(last$CP, na.rm = TRUE))
  })

  output$auc <- renderText({
    d        <- sim_data()
    interval <- as.numeric(input$interval)
    t_start  <- (as.numeric(input$n_days) - 1) * 24
    last     <- d |> dplyr::filter(time >= t_start, time <= t_start + interval)
    auc      <- sum(diff(last$time) * (head(last$CP, -1) + tail(last$CP, -1)) / 2)
    sprintf("%.1f", auc)
  })

  output$thalf <- renderText({
    CLi <- 0.901 * (input$wt / 70)^0.75 * preg_factor() * as.numeric(input$ddi)
    Vi  <- 17.4 * (input$wt / 70)
    sprintf("%.1f", log(2) / (CLi / Vi))
  })

  output$pkPlot <- renderPlot({
    d       <- sim_data()
    ic90pa  <- 0.064  # protein-adjusted IC90 in µg/mL
    interval <- as.numeric(input$interval)

    preg_labels <- c("none" = "Non-Pregnant", "t2" = "2nd Trimester", "t3" = "3rd Trimester")
    dose_label  <- paste0(input$dose, " mg ",
                    ifelse(interval == 24, "QD", "BID"),
                    " — ", preg_labels[input$pregnancy])

    CLi <- 0.901 * (input$wt / 70)^0.75 * preg_factor() * as.numeric(input$ddi)
    Vi  <- 17.4 * (input$wt / 70)

    p <- ggplot(d, aes(x = time_h, y = CP)) +
      geom_hline(yintercept = ic90pa, linetype = "dashed",
                 color = "#ef4444", alpha = 0.8, linewidth = 0.8) +
      annotate("text", x = max(d$time_h) * 0.02, y = ic90pa * 1.25,
               label = paste0("IC90-PA: ", ic90pa, " µg/mL"),
               hjust = 0, size = 3.5, color = "#ef4444") +
      geom_line(color = "#8b5cf6", linewidth = 0.9) +
      labs(
        x        = "Time (hours)",
        y        = "Plasma Concentration (µg/mL)",
        title    = paste0("Dolutegravir ", dose_label),
        subtitle = paste0("Weight: ", input$wt, " kg  |  CL/F: ",
                          round(CLi, 2), " L/h  |  t½: ",
                          round(log(2) / (CLi / Vi), 1), " h")
      ) +
      theme_minimal(base_size = 14) +
      theme(
        plot.title    = element_text(face = "bold"),
        plot.subtitle = element_text(color = "#6c757d", size = 11)
      )

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

shinyApp(ui = ui, server = server)