library(shiny)
library(bslib)
library(mrgsolve)
library(dplyr)
library(ggplot2)
# ── mrgsolve model ──────────────────────────────────────────────────────────
model_code <- '
$PARAM @annotated
CL   : 10.3  : Apparent clearance (L/h)
Vc   : 16.9  : Central volume of distribution (L)
Vp   : 166   : Peripheral volume of distribution (L)
Q    : 17.4  : Intercompartmental clearance (L/h)
KA   : 0.0718 : First-order absorption rate constant (1/h)
F1   : 0.372 : Oral bioavailability (fraction, fed state)
D1   : 0.619 : Duration of zero-order absorption (h)
CLCR : 90    : Creatinine clearance (mL/min)
ALB  : 4.0   : Albumin (g/dL)

$CMT @annotated
DEPOT  : Oral absorption depot [mg]
CENT   : Central compartment [mg]
PERIPH : Peripheral compartment [mg]

$MAIN
// Covariate-adjusted clearance (renal function + albumin)
double CLi = CL * pow(CLCR/90.0, 0.30) * pow(ALB/4.0, 0.25);
F_DEPOT = F1;
D_DEPOT = D1;

$ODE
dxdt_DEPOT  = -KA * DEPOT;
dxdt_CENT   = KA * DEPOT - (CLi/Vc) * CENT - (Q/Vc) * CENT + (Q/Vp) * PERIPH;
dxdt_PERIPH = (Q/Vc) * CENT - (Q/Vp) * PERIPH;

$TABLE
double CP = (CENT / Vc) * 1000.0;   // ng/mL

$CAPTURE CP CLi
'

mod <- mcode("rucaparib", model_code, quiet = TRUE)

# ── App 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 = "Rucaparib (Rubraca) PK Simulator",
  theme = app_theme,

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

    h6("💊 Dosing"),
    sliderInput("dose", "Dose (mg)",
                min = 200, max = 800, value = 600, step = 200),
    selectInput("interval", "Dosing Interval",
                choices = c("BID — Q12H" = "12", "QD — Q24H" = "24"),
                selected = "12"),
    numericInput("n_days", "Duration (days)", value = 14, min = 1, max = 28),

    hr(),
    h6("👤 Patient Characteristics"),
    sliderInput("clcr", "Creatinine Clearance (mL/min)",
                min = 30, max = 120, value = 90, step = 5),
    sliderInput("alb", "Albumin (g/dL)",
                min = 2.5, max = 5.0, value = 4.0, step = 0.1),

    hr(),
    h6("🍽️ Food Effect"),
    selectInput("food", "Dosing Condition",
                choices = c(
                  "Fed — typical" = "fed",
                  "Fasted"        = "fasted",
                  "High-fat meal (>480 mg)" = "hfm"
                ),
                selected = "fed"),

    hr(),
    checkboxInput("log_scale", "Log Scale (Y-axis)", value = FALSE),
    checkboxInput("show_ref",  "Show 600 mg BID Cavg reference", value = TRUE)
  ),

  navset_card_underline(
    title = "Rucaparib Population PK Simulator",

    # ── Tab 1: Simulation ──────────────────────────────────────────────────
    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 (ng/mL)")),
        div(class = "metric-card metric-warning",
            div(class = "metric-value", textOutput("ctrough")),
            div(class = "metric-label", "Ctrough,ss (ng/mL)")),
        div(class = "metric-card metric-primary",
            div(class = "metric-value", textOutput("auc")),
            div(class = "metric-label", "AUC\u2080-\u03c4,ss (ng\u00b7h/mL)")),
        div(class = "metric-card metric-info",
            div(class = "metric-value", textOutput("thalf")),
            div(class = "metric-label", "t\u00bd terminal (h)"))
      ),

      card(
        full_screen = TRUE,
        plotOutput("pkPlot", height = "500px")
      )
    ),

    # ── Tab 2: Model Information ───────────────────────────────────────────
    nav_panel("Model Information",
      div(class = "ref-box",
        markdown("
## Rucaparib (Rubraca) — 2-Compartment Population PK Model

**Drug Class:** PARP inhibitor (poly ADP-ribose polymerase)
**Indication:** BRCA1/2-mutated advanced ovarian cancer (≥ 2 prior platinum-based regimens)
**NDA:** 209115 (FDA approval: December 2016)

---

### Model Structure
- **Type:** Two-compartment with sequential zero-order → first-order oral absorption
- **Dataset:** 458 patients; 3 studies — A4991014, CO-338-010 (Study 10), ARIEL2
- **Software:** NONMEM 7.3 / R 3.3.0

### Population PK Parameter Estimates

| Parameter | Estimate | Description |
|-----------|----------|-------------|
| CL | 10.3 L/h | Apparent oral clearance |
| Vc | 16.9 L | Central volume of distribution |
| Vp | 166 L | Peripheral volume of distribution |
| Q | 17.4 L/h | Intercompartmental clearance |
| Ka | 0.0718 h⁻¹ | First-order absorption rate constant |
| F1 | 37.2% | Oral bioavailability (fed, typical) |
| D1 | 0.619 h | Zero-order absorption duration |
| t½ | ~17–19 h | Terminal half-life |

### Covariate Effects on Clearance
| Covariate | Direction | Magnitude |
|-----------|-----------|-----------|
| CLCR ↑ | CL ↑ | ~26% across range |
| Albumin ↑ | CL ↑ | ~18% across range |
| Mild renal impairment | AUC ↑ | ~15% |
| Moderate renal impairment | AUC ↑ | ~33% |

### Food Effect
| Condition | Dose | F1 |
|-----------|------|----|
| Fed (typical) | all | 37.2% |
| Fasted | ≤480 mg | 29.0% |
| Fasted | >480 mg | 32.6% |
| High-fat meal | >480 mg | 51.7% |

### Steady-State Exposures at 600 mg BID
| Metric | Value |
|--------|-------|
| Cavg,ss (AUCavg1W) | ~1333 ng/mL |
| Predicted 200 mg BID Cavg | ~447 ng/mL |
| Predicted 400 mg BID Cavg | ~893 ng/mL |

### Notes
- CYP1A2 and CYP2D6 phenotypes did not significantly impact rucaparib PK
- PPI co-medication increases F1 by ~15% (not clinically meaningful)
- Ka decreased with increasing dose levels
        ")
      )
    ),

    # ── Tab 3: References ──────────────────────────────────────────────────
    nav_panel("References",
      div(class = "ref-box",
        tags$h5("\U0001f4da Key References"),
        tags$ol(
          tags$li(
            "FDA NDA 209115 Multi-Discipline Review — Rucaparib (Rubraca), 2016. ",
            tags$a(href = "https://www.accessdata.fda.gov/drugsatfda_docs/nda/2016/209115Orig1s000MultiDisciplineR.pdf",
                   target = "_blank", "FDA DARRTS")
          ),
          tags$li(
            "Xiao JJ et al. (2022). Population pharmacokinetics of rucaparib in patients with advanced ovarian cancer or other solid tumors. ",
            tags$em("Cancer Chemother Pharmacol."),
            " doi:10.1007/s00280-022-04413-7"
          ),
          tags$li(
            "Kristeleit R et al. (2022). Clinical Pharmacokinetics and Pharmacodynamics of Rucaparib. ",
            tags$em("Clin Pharmacokinet."),
            " doi:10.1007/s40262-022-01157-8"
          ),
          tags$li(
            "Swisher EM et al. (2017). Rucaparib in relapsed, platinum-sensitive high-grade ovarian carcinoma (ARIEL2 Part 1). ",
            tags$em("Lancet Oncol."), " 18(1):75-87."
          )
        ),
        tags$h5("\U0001f48a Drug Information"),
        tags$ul(
          tags$li(tags$strong("Brand Name:"), " Rubraca\u00ae (Clovis Oncology)"),
          tags$li(tags$strong("Class:"), " PARP inhibitor"),
          tags$li(tags$strong("Approved dose:"), " 600 mg BID orally (with or without food)"),
          tags$li(tags$strong("Dose reductions:"), " 500 → 400 → 300 mg BID for toxicity"),
          tags$li(tags$strong("Metabolism:"), " CYP1A2, CYP2D6, CYP3A4 (minor); also glucuronidation"),
          tags$li(tags$strong("Protein binding:"), " ~70%"),
          tags$li(tags$strong("Time to Cmax:"), " ~1.9 h (median)"),
          tags$li(tags$strong("Indication:"), " BRCA1/2-mutated advanced ovarian cancer (≥2 prior platinum-based regimens)")
        )
      )
    )
  ),

  # ── Footer ─────────────────────────────────────────────────────────────────
  div(
    style = paste0(
      "text-align:center; padding:20px; margin-top:30px;",
      " border-top:1px solid #e9ecef; color:#6c757d; font-size:12px;"
    ),
    "Powered by ",
    tags$a(href = "https://www.pkpdbuilder.com", target = "_blank",
           style = "color:#8b5cf6; font-weight:500;", "PKPDBuilder.com"),
    " \u2022 Built by Sunny \u2600\ufe0f (Husain Attarwala\u2019s AI Assistant)",
    tags$br(),
    tags$span(
      style = "font-size:10px;",
      "For research and educational purposes only. Not for clinical decision-making."
    )
  )
)

# ── Server ───────────────────────────────────────────────────────────────────
server <- function(input, output, session) {

  # Bioavailability adjusted for food and dose
  f1_reactive <- reactive({
    dose <- input$dose
    food <- input$food
    if (food == "fasted") {
      if (dose > 480) 0.326 else 0.290
    } else if (food == "hfm") {
      if (dose > 480) 0.517 else 0.290
    } else {
      0.372
    }
  })

  # Full PK simulation
  sim_data <- reactive({
    shiny::req(input$dose, input$interval, input$n_days, input$clcr, input$alb)
    ii      <- as.numeric(input$interval)
    n_doses <- ceiling(input$n_days * 24 / ii)
    ev1     <- ev(amt = input$dose, cmt = 1, ii = ii, addl = n_doses - 1)

    mod %>%
      param(CLCR = input$clcr, ALB = input$alb, F1 = f1_reactive()) %>%
      ev(ev1) %>%
      mrgsim(end = input$n_days * 24, delta = 0.1) %>%
      as.data.frame()
  })

  # Last-day (steady-state) slice
  ss_data <- reactive({
    d <- sim_data()
    last_start <- (input$n_days - 1) * 24
    dplyr::filter(d, time >= last_start)
  })

  # Terminal half-life (analytical)
  thalf_val <- reactive({
    shiny::req(input$clcr, input$alb)
    CLi  <- 10.3 * (input$clcr / 90)^0.30 * (input$alb / 4.0)^0.25
    k10  <- CLi / 16.9
    k12  <- 17.4 / 16.9
    k21  <- 17.4 / 166
    s    <- k10 + k12 + k21
    disc <- sqrt(s^2 - 4 * k10 * k21)
    beta <- (s - disc) / 2
    log(2) / beta
  })

  output$cmax <- renderText({
    shiny::req(ss_data())
    sprintf("%.0f", max(ss_data()$CP, na.rm = TRUE))
  })

  output$ctrough <- renderText({
    shiny::req(ss_data())
    sprintf("%.0f", min(ss_data()$CP, na.rm = TRUE))
  })

  output$auc <- renderText({
    shiny::req(sim_data())
    ii         <- as.numeric(input$interval)
    last_start <- (input$n_days - 1) * 24
    last <- dplyr::filter(sim_data(), time >= last_start, time <= last_start + ii)
    if (nrow(last) < 2) return("\u2014")
    auc <- sum(diff(last$time) * (head(last$CP, -1) + tail(last$CP, -1)) / 2)
    sprintf("%.0f", auc)
  })

  output$thalf <- renderText({
    sprintf("%.1f", thalf_val())
  })

  output$pkPlot <- renderPlot({
    shiny::req(sim_data())
    d  <- sim_data()
    ii <- as.numeric(input$interval)
    dose_label <- paste0(input$dose, " mg Q", ii, "H")

    p <- ggplot(d, aes(x = time, y = CP)) +
      geom_line(color = "#8b5cf6", linewidth = 0.9) +
      labs(
        x       = "Time (hours)",
        y       = "Rucaparib Concentration (ng/mL)",
        title   = paste0("Rucaparib ", dose_label, " \u2014 Population PK Simulation"),
        caption = paste0(
          "2-CMT sequential zero-order/first-order absorption | ",
          "CLCR = ", input$clcr, " mL/min | ALB = ", input$alb, " g/dL | ",
          "Source: FDA NDA 209115"
        )
      ) +
      theme_minimal(base_size = 14) +
      theme(plot.caption = element_text(size = 9, color = "#6c757d"))

    # Reference Cavg,ss for 600 mg BID
    if (isTRUE(input$show_ref) && !(input$dose == 600 && ii == 12)) {
      p <- p +
        geom_hline(yintercept = 1333, linetype = "dashed",
                   color = "#6c757d", linewidth = 0.6, alpha = 0.8) +
        annotate("text",
                 x     = max(d$time, na.rm = TRUE) * 0.02,
                 y     = 1460,
                 label = "600 mg BID Cavg,ss ref (1333 ng/mL)",
                 hjust = 0, size = 3.2, color = "#6c757d")
    }

    if (isTRUE(input$log_scale)) {
      d_pos <- dplyr::filter(d, CP > 0)
      p <- p %+% d_pos + scale_y_log10(
        labels = scales::label_number(accuracy = 1)
      )
    }

    p
  })
}

shinyApp(ui = ui, server = server)