use <- function(pkg, attach = TRUE) {
  if (attach) {
    library(pkg, character.only = TRUE)
  } else {
    requireNamespace(pkg, quietly = TRUE)
  }
}

use("shiny", attach = TRUE)
use("bslib", attach = TRUE)
use("mrgsolve", attach = TRUE)
use("dplyr", attach = TRUE)
use("ggplot2", attach = TRUE)

model_code <- '
$PARAM @annotated
CL    : 0.2359 : Clearance (L/day)
V     : 7.84   : Volume of distribution (L)
KA    : 1.043  : Absorption rate constant (1/day)
F1    : 0.70   : Absolute bioavailability fraction
WT    : 87     : Body weight (kg)
CLWT  : 1.11   : Body weight exponent on clearance
VWT   : 1.00   : Body weight exponent on volume
CLMULT: 1.00   : Disease-specific clearance multiplier
VMULT : 1.00   : Disease-specific volume multiplier

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

$MAIN
double wt_ratio = WT / 87.0;
double CLi = CL * pow(wt_ratio, CLWT) * CLMULT;
double Vi  = V  * pow(wt_ratio, VWT) * VMULT;
F_DEPOT = F1;

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

$TABLE
double CP = CENT / Vi;

double CL_OUT = CLi;
double V_OUT  = Vi;

$CAPTURE @annotated
CP     : Plasma concentration (mg/L = ug/mL)
CL_OUT : Individual clearance (L/day)
V_OUT  : Individual volume (L)
'

mod <- mcode("bimekizumab_pkpd_317", model_code)

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;
    }
    .small-note {
      color: #6c757d;
      font-size: 12px;
      margin-top: 8px;
    }
    .info-grid td {
      padding: 6px 10px;
      vertical-align: top;
      border-bottom: 1px solid #eef2f7;
    }
    .info-grid td:first-child {
      font-weight: 600;
      width: 220px;
    }
  ")

regimen_choices <- c(
  "Single 320 mg SC dose (PK reference)" = "single_320",
  "Plaque psoriasis label regimen" = "pso_standard",
  "Plaque psoriasis >=120 kg maintenance option" = "pso_high_weight",
  "PsA / nr-axSpA / AS label regimen" = "immune_q4w",
  "Hidradenitis suppurativa label regimen" = "hs_standard",
  "Custom fixed-interval SC regimen" = "custom"
)

build_regimen_schedule <- function(regimen, duration_weeks, custom_dose = 160, custom_interval = 4) {
  duration_days <- duration_weeks * 7

  if (regimen == "single_320") {
    times <- 0
    dose <- 320
    current_interval <- 28
    label <- "Single 320 mg SC dose"
    cl_mult <- 1.00
    v_mult <- 1.00
  } else if (regimen == "pso_standard") {
    induction <- c(0, 4, 8, 12, 16) * 7
    maintenance <- seq(24, ceiling(duration_weeks) + 8, by = 8) * 7
    times <- sort(unique(c(induction, maintenance)))
    times <- times[times <= duration_days]
    dose <- 320
    current_interval <- if (length(times) > 1 && max(times) >= 24 * 7) 56 else 28
    label <- "Plaque psoriasis: 320 mg at Weeks 0, 4, 8, 12, 16 then every 8 weeks"
    cl_mult <- 1.00
    v_mult <- 1.00
  } else if (regimen == "pso_high_weight") {
    induction <- c(0, 4, 8, 12, 16) * 7
    maintenance <- seq(20, ceiling(duration_weeks) + 4, by = 4) * 7
    times <- sort(unique(c(induction, maintenance)))
    times <- times[times <= duration_days]
    dose <- 320
    current_interval <- 28
    label <- "Plaque psoriasis >=120 kg option: 320 mg at Weeks 0, 4, 8, 12, 16 then every 4 weeks"
    cl_mult <- 1.00
    v_mult <- 1.00
  } else if (regimen == "immune_q4w") {
    times <- seq(0, duration_days, by = 28)
    dose <- 160
    current_interval <- 28
    label <- "PsA / nr-axSpA / AS: 160 mg every 4 weeks"
    cl_mult <- 1.00
    v_mult <- 1.00
  } else if (regimen == "hs_standard") {
    induction <- seq(0, 16, by = 2) * 7
    maintenance <- seq(20, ceiling(duration_weeks) + 4, by = 4) * 7
    times <- sort(unique(c(induction, maintenance)))
    times <- times[times <= duration_days]
    dose <- 320
    current_interval <- if (length(times) > 1 && max(times) >= 20 * 7) 28 else 14
    label <- "HS: 320 mg every 2 weeks to Week 16, then every 4 weeks"
    cl_mult <- 1.31
    v_mult <- 1.18
  } else {
    interval_days <- custom_interval * 7
    times <- seq(0, duration_days, by = interval_days)
    dose <- custom_dose
    current_interval <- interval_days
    label <- paste0("Custom SC regimen: ", custom_dose, " mg every ", custom_interval, " weeks")
    cl_mult <- 1.00
    v_mult <- 1.00
  }

  if (length(times) == 0) {
    times <- 0
  }

  list(
    times = times,
    dose = dose,
    current_interval = current_interval,
    label = label,
    cl_mult = cl_mult,
    v_mult = v_mult
  )
}

trap_auc <- function(time, conc) {
  if (length(time) < 2 || length(conc) < 2) {
    return(NA_real_)
  }
  sum(diff(time) * (head(conc, -1) + tail(conc, -1)) / 2)
}

ui <- page_sidebar(
  title = "BIMZELX (Bimekizumab) PK Simulator",
  theme = app_theme,
  sidebar = sidebar(
    title = "Simulation Settings",
    width = 340,
    selectInput("regimen", "Label regimen", choices = regimen_choices, selected = "single_320"),
    conditionalPanel(
      condition = "input.regimen == 'custom'",
      sliderInput("custom_dose", "Dose (mg)", min = 80, max = 640, value = 160, step = 20),
      sliderInput("custom_interval", "Interval (weeks)", min = 1, max = 12, value = 4, step = 1)
    ),
    sliderInput("wt", "Body weight (kg)", min = 40, max = 160, value = 87, step = 1),
    selectInput(
      "population_type",
      "Population PK context",
      choices = c(
        "Auto from regimen" = "auto",
        "Standard PSO / PsA / nr-axSpA / AS" = "standard",
        "HS population" = "hs"
      ),
      selected = "auto"
    ),
    numericInput("duration_weeks", "Simulation duration (weeks)", value = 32, min = 4, max = 104, step = 4),
    checkboxInput("log_scale", "Log scale (Y-axis)", value = FALSE),
    div(class = "small-note", "Weight is modeled as an exposure covariate. Select HS population to apply the label-reported higher apparent CL/F and V/F seen in hidradenitis suppurativa.")
  ),
  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 (ug/mL)")),
    div(class = "metric-card metric-warning",
        div(class = "metric-value", textOutput("ctrough")),
        div(class = "metric-label", "Ctrough (ug/mL)")),
    div(class = "metric-card metric-primary",
        div(class = "metric-value", textOutput("auc")),
        div(class = "metric-label", "AUCtau (ug*day/mL)")),
    div(class = "metric-card metric-info",
        div(class = "metric-value", textOutput("thalf")),
        div(class = "metric-label", "t1/2 (days)"))
  ),
  card(
    card_header("Concentration-Time Profile"),
    full_screen = TRUE,
    plotOutput("pkPlot", height = "500px"),
    div(class = "small-note", textOutput("plot_note"))
  ),
  navset_card_underline(
    title = "Drug Information",
    nav_panel("Model Information", uiOutput("model_info")),
    nav_panel("References", uiOutput("references"))
  ),
  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_bundle <- reactive({
    schedule <- build_regimen_schedule(
      regimen = input$regimen,
      duration_weeks = input$duration_weeks,
      custom_dose = input$custom_dose,
      custom_interval = input$custom_interval
    )

    event_df <- data.frame(
      ID = 1,
      time = schedule$times,
      amt = schedule$dose,
      cmt = 1,
      evid = 1
    )

    sim_end <- max(input$duration_weeks * 7, max(schedule$times) + schedule$current_interval)

    cl_mult <- if (input$population_type == "auto") schedule$cl_mult else if (input$population_type == "hs") 1.31 else 1.00
    v_mult <- if (input$population_type == "auto") schedule$v_mult else if (input$population_type == "hs") 1.18 else 1.00

    sim <- mod %>%
      param(WT = input$wt, CLMULT = cl_mult, VMULT = v_mult) %>%
      data_set(event_df) %>%
      mrgsim(end = sim_end, delta = 0.25) %>%
      as.data.frame() |>
      mutate(
        time_days = time,
        time_weeks = time / 7
      )

    last_dose_time <- max(schedule$times)
    metric_end <- last_dose_time + schedule$current_interval
    interval_data <- sim |>
      dplyr::filter(time_days >= last_dose_time, time_days <= metric_end)

    list(
      sim = sim,
      schedule = schedule,
      plot_end = input$duration_weeks * 7,
      interval_data = interval_data,
      last_dose_time = last_dose_time,
      metric_end = metric_end,
      cl_mult = cl_mult,
      v_mult = v_mult
    )
  })

  output$cmax <- renderText({
    d <- sim_bundle()$interval_data
    shiny::req(nrow(d) > 0)
    sprintf("%.1f", max(d$CP, na.rm = TRUE))
  })

  output$ctrough <- renderText({
    d <- sim_bundle()$interval_data
    shiny::req(nrow(d) > 0)
    sprintf("%.1f", d$CP[nrow(d)])
  })

  output$auc <- renderText({
    d <- sim_bundle()$interval_data
    shiny::req(nrow(d) > 1)
    auc_val <- trap_auc(d$time_days, d$CP)
    sprintf("%.1f", auc_val)
  })

  output$thalf <- renderText({
    bundle <- sim_bundle()
    cl_i <- 0.2359 * (input$wt / 87)^1.11 * bundle$cl_mult
    v_i <- 7.84 * (input$wt / 87)^1.00 * bundle$v_mult
    sprintf("%.1f", log(2) * v_i / cl_i)
  })

  output$plot_note <- renderText({
    paste0(
      "Metrics are calculated over the final dosing interval after the last simulated dose. Current regimen: ",
      sim_bundle()$schedule$label
    )
  })

  output$pkPlot <- renderPlot({
    bundle <- sim_bundle()
    d <- bundle$sim |>
      dplyr::filter(time_days <= bundle$plot_end)
    shiny::req(nrow(d) > 0)

    d_plot <- if (input$log_scale) {
      d |>
        dplyr::filter(CP > 0.001)
    } else {
      d
    }
    shiny::req(nrow(d_plot) > 0)

    dose_df <- data.frame(time_weeks = bundle$schedule$times / 7)

    p <- ggplot(d_plot, aes(x = time_weeks, y = CP)) +
      geom_vline(data = dose_df, aes(xintercept = time_weeks), color = "#cbd5e1", linetype = "dashed", linewidth = 0.4) +
      geom_line(color = "#8b5cf6", linewidth = 1) +
      labs(
        x = "Time (weeks)",
        y = "Plasma concentration (ug/mL)",
        title = "Bimekizumab concentration-time profile"
      ) +
      theme_minimal(base_size = 14)

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

    if (input$regimen == "single_320") {
      p <- p +
        geom_hline(yintercept = 25, color = "#10b981", linetype = "dotted", linewidth = 0.8) +
        annotate("text", x = 1.5, y = 27, label = "Label median Cmax ≈ 25 ug/mL", color = "#10b981", hjust = 0, size = 3.4)
    }

    p
  })

  output$model_info <- renderUI({
    bundle <- sim_bundle()
    info <- bundle$schedule
    if (input$population_type == "hs" || (input$population_type == "auto" && input$regimen == "hs_standard")) {
      disease_note <- "HS PK context applies label-based higher apparent clearance (+31%) and volume (+18%) to reflect lower exposure in hidradenitis suppurativa subjects."
      population_label <- "HS population"
    } else {
      disease_note <- "Standard population PK context uses the shared estimates reported across plaque psoriasis, psoriatic arthritis, nr-axSpA, and ankylosing spondylitis."
      population_label <- "Standard indications"
    }

    div(
      tags$h4("BIMZELX — label-derived 1-compartment SC PopPK model"),
      tags$p("This simulator uses a simplified first-order absorption, one-compartment model calibrated to the FDA prescribing information for bimekizumab-bkzx."),
      tags$table(
        class = "info-grid",
        tags$tr(tags$td("Model structure"), tags$td("1-compartment SC absorption model")),
        tags$tr(tags$td("Absolute bioavailability"), tags$td("70%")),
        tags$tr(tags$td("Apparent clearance (CL/F)"), tags$td("0.337 L/day")),
        tags$tr(tags$td("Apparent volume (V/F)"), tags$td("11.2 L")),
        tags$tr(tags$td("Model CL"), tags$td("0.236 L/day after separating F")),
        tags$tr(tags$td("Model V"), tags$td("7.84 L after separating F")),
        tags$tr(tags$td("Absorption rate (Ka)"), tags$td("1.043 day^-1, chosen to match Tmax ~3-4 days")),
        tags$tr(tags$td("Terminal half-life"), tags$td("23 days at 87 kg reference weight")),
        tags$tr(tags$td("Single-dose PK anchor"), tags$td("320 mg SC: median peak ~25 ug/mL at 3-4 days")),
        tags$tr(tags$td("Weight effect"), tags$td("Clearance scaled to approximate >=120 kg exposure reduction reported in label")),
        tags$tr(tags$td("Population context"), tags$td(population_label)),
        tags$tr(tags$td("Current regimen"), tags$td(info$label))
      ),
      tags$div(
        class = "ref-box",
        tags$strong("Clinical interpretation"),
        tags$ul(
          tags$li("Plaque psoriasis: 320 mg at Weeks 0, 4, 8, 12, and 16, then every 8 weeks; consider every 4 weeks after Week 16 when body weight is >=120 kg."),
          tags$li("Psoriatic arthritis, non-radiographic axial spondyloarthritis, and ankylosing spondylitis: 160 mg every 4 weeks."),
          tags$li("Hidradenitis suppurativa: 320 mg every 2 weeks through Week 16, then every 4 weeks."),
          tags$li(disease_note)
        )
      )
    )
  })

  output$references <- renderUI({
    div(
      class = "ref-box",
      tags$h5("Key references"),
      tags$ol(
        tags$li(
          tags$a(
            href = "https://www.accessdata.fda.gov/drugsatfda_docs/label/2024/761151s005s006s007lbl.pdf",
            target = "_blank",
            "BIMZELX (bimekizumab-bkzx) prescribing information"
          ),
          " — label-derived PK parameters, dose regimens, and exposure summaries."
        ),
        tags$li(
          tags$a(
            href = "https://www.ucb-usa.com/bimzelx-prescribing-information.pdf",
            target = "_blank",
            "UCB prescribing information mirror"
          ),
          " — corroborates label PK values and indication-specific dosing."
        )
      ),
      tags$h5("What this app covers"),
      tags$ul(
        tags$li("Subcutaneous bimekizumab exposure under labeled regimens and custom fixed-interval regimens."),
        tags$li("Weight-dependent exposure changes and lower HS exposure via disease-specific CL/F and V/F multipliers."),
        tags$li("Exploratory PK simulation only; no direct efficacy or safety threshold modeling.")
      )
    )
  })
}

shinyApp(ui = ui, server = server)