from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm, mm
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, PageBreak, KeepTogether
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
from reportlab.platypus.flowables import HRFlowable
from reportlab.pdfgen import canvas
from reportlab.lib.colors import HexColor

# ── Colour palette ──────────────────────────────────────────────────────────
C_DARK_BLUE   = HexColor("#1A3C5E")
C_MED_BLUE    = HexColor("#2E6DA4")
C_LIGHT_BLUE  = HexColor("#D6E8F7")
C_ACCENT      = HexColor("#E8A020")
C_GREEN       = HexColor("#2E7D32")
C_GREEN_LIGHT = HexColor("#E8F5E9")
C_RED         = HexColor("#C62828")
C_RED_LIGHT   = HexColor("#FFEBEE")
C_PURPLE      = HexColor("#6A1B9A")
C_PURPLE_LIGHT= HexColor("#F3E5F5")
C_ORANGE_LIGHT= HexColor("#FFF3E0")
C_GREY_BG     = HexColor("#F5F7FA")
C_GREY_LINE   = HexColor("#CFD8DC")
C_WHITE       = colors.white
C_BLACK       = colors.black

W, H = A4

# ── Page layout ─────────────────────────────────────────────────────────────
MARGIN = 1.8*cm

def header_footer(canvas_obj, doc):
    canvas_obj.saveState()
    # Header bar
    canvas_obj.setFillColor(C_DARK_BLUE)
    canvas_obj.rect(0, H - 1.2*cm, W, 1.2*cm, fill=1, stroke=0)
    canvas_obj.setFillColor(C_WHITE)
    canvas_obj.setFont("Helvetica-Bold", 9)
    canvas_obj.drawString(MARGIN, H - 0.78*cm, "PHARMACOLOGY STUDY GUIDE  |  Exam Prep")
    canvas_obj.setFont("Helvetica", 8)
    canvas_obj.drawRightString(W - MARGIN, H - 0.78*cm, f"Page {doc.page}")

    # Footer bar
    canvas_obj.setFillColor(C_DARK_BLUE)
    canvas_obj.rect(0, 0, W, 0.9*cm, fill=1, stroke=0)
    canvas_obj.setFillColor(C_WHITE)
    canvas_obj.setFont("Helvetica", 7.5)
    canvas_obj.drawCentredString(W/2, 0.32*cm, "Sources: Lippincott Pharmacology | Ganong's Physiology | Katzung | Wills Eye Manual")
    canvas_obj.restoreState()

# ── Styles ───────────────────────────────────────────────────────────────────
styles = getSampleStyleSheet()
body_w = W - 2*MARGIN

def S(name, **kw):
    base = styles.get(name, styles["Normal"])
    return ParagraphStyle(name + str(kw), parent=base, **kw)

cover_title   = S("Title",    fontName="Helvetica-Bold",  fontSize=36, textColor=C_WHITE,      alignment=TA_CENTER, leading=44)
cover_sub     = S("Normal",   fontName="Helvetica",        fontSize=14, textColor=C_LIGHT_BLUE, alignment=TA_CENTER, leading=20)
cover_by      = S("Normal",   fontName="Helvetica-Oblique",fontSize=10, textColor=HexColor("#90CAF9"), alignment=TA_CENTER)
h1            = S("Heading1", fontName="Helvetica-Bold",  fontSize=16, textColor=C_WHITE,      spaceAfter=4,  spaceBefore=14, leading=20)
h2            = S("Heading2", fontName="Helvetica-Bold",  fontSize=12, textColor=C_DARK_BLUE,  spaceAfter=4,  spaceBefore=10, leading=16)
h3            = S("Heading3", fontName="Helvetica-Bold",  fontSize=10.5, textColor=C_MED_BLUE, spaceAfter=3,  spaceBefore=7,  leading=14)
body          = S("Normal",   fontName="Helvetica",        fontSize=9.5, textColor=C_BLACK,     spaceAfter=4,  leading=14, alignment=TA_JUSTIFY)
bullet        = S("Normal",   fontName="Helvetica",        fontSize=9.5, textColor=C_BLACK,     leftIndent=14, firstLineIndent=-10, spaceAfter=3, leading=13)
bullet_b      = S("Normal",   fontName="Helvetica-Bold",   fontSize=9.5, textColor=C_DARK_BLUE, leftIndent=14, firstLineIndent=-10, spaceAfter=2, leading=13)
note_style    = S("Normal",   fontName="Helvetica-Oblique",fontSize=8.5, textColor=C_RED,       leftIndent=8,  spaceAfter=3, leading=12)
mnemonic_s    = S("Normal",   fontName="Helvetica-Bold",   fontSize=11,  textColor=C_GREEN,     alignment=TA_CENTER, spaceAfter=2)
keypoint_s    = S("Normal",   fontName="Helvetica-Bold",   fontSize=9.5, textColor=C_RED,       leftIndent=10, spaceAfter=3, leading=13)
small_head    = S("Normal",   fontName="Helvetica-Bold",   fontSize=9,   textColor=C_WHITE)
toc_style     = S("Normal",   fontName="Helvetica",        fontSize=10,  textColor=C_DARK_BLUE, leading=18)
toc_num       = S("Normal",   fontName="Helvetica-Bold",   fontSize=10,  textColor=C_ACCENT)

# ── Helper flowables ─────────────────────────────────────────────────────────
def section_banner(text, color=C_DARK_BLUE, text_color=C_WHITE, num=""):
    data = [[Paragraph(f"{'<b>'+num+'  </b>' if num else ''}{text}", S("Normal", fontName="Helvetica-Bold", fontSize=14, textColor=text_color, leading=18))]]
    t = Table(data, colWidths=[body_w])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), color),
        ("TOPPADDING",  (0,0), (-1,-1), 10),
        ("BOTTOMPADDING",(0,0),(-1,-1), 10),
        ("LEFTPADDING", (0,0), (-1,-1), 14),
        ("RIGHTPADDING",(0,0), (-1,-1), 14),
        ("ROWBACKGROUNDS",(0,0),(-1,-1),[color]),
    ]))
    return t

def info_box(title, content_rows, bg=C_LIGHT_BLUE, title_bg=C_MED_BLUE):
    """Box with coloured header and bullet rows."""
    rows = [[Paragraph(title, S("Normal", fontName="Helvetica-Bold", fontSize=10, textColor=C_WHITE))]]
    for r in content_rows:
        rows.append([Paragraph(r, body)])
    col_w = [body_w]
    t = Table(rows, colWidths=col_w)
    style = [
        ("BACKGROUND", (0,0), (-1,0), title_bg),
        ("BACKGROUND", (0,1), (-1,-1), bg),
        ("TOPPADDING",  (0,0), (-1,-1), 5),
        ("BOTTOMPADDING",(0,0),(-1,-1), 5),
        ("LEFTPADDING", (0,0), (-1,-1), 10),
        ("RIGHTPADDING",(0,0), (-1,-1), 10),
        ("BOX", (0,0), (-1,-1), 0.8, C_MED_BLUE),
        ("LINEBEFORE", (0,0), (-1,-1), 0.4, C_GREY_LINE),
    ]
    t.setStyle(TableStyle(style))
    return t

def key_point_box(text, color=C_ACCENT):
    data = [[Paragraph("★  KEY POINT", S("Normal", fontName="Helvetica-Bold", fontSize=8.5, textColor=C_DARK_BLUE)),
             Paragraph(text, body)]]
    t = Table(data, colWidths=[2.2*cm, body_w-2.2*cm])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), C_ORANGE_LIGHT),
        ("LEFTPADDING", (0,0), (-1,-1), 8),
        ("RIGHTPADDING",(0,0),(-1,-1), 8),
        ("TOPPADDING",  (0,0),(-1,-1), 6),
        ("BOTTOMPADDING",(0,0),(-1,-1), 6),
        ("BOX", (0,0),(-1,-1), 1, C_ACCENT),
        ("VALIGN", (0,0),(-1,-1), "MIDDLE"),
    ]))
    return t

def mnemonic_box(mnemonic, meaning):
    rows = [[Paragraph("MNEMONIC", S("Normal", fontName="Helvetica-Bold", fontSize=8.5, textColor=C_WHITE))]]
    rows.append([Paragraph(f'<font color="#2E7D32"><b>{mnemonic}</b></font>', S("Normal", fontName="Helvetica-Bold", fontSize=13, textColor=C_GREEN, alignment=TA_CENTER))])
    for line in meaning:
        rows.append([Paragraph(line, S("Normal", fontSize=9.5, leading=13))])
    t = Table(rows, colWidths=[body_w])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (0,0), C_GREEN),
        ("BACKGROUND", (0,1), (-1,-1), C_GREEN_LIGHT),
        ("TOPPADDING",  (0,0),(-1,-1), 5),
        ("BOTTOMPADDING",(0,0),(-1,-1), 5),
        ("LEFTPADDING", (0,0),(-1,-1), 12),
        ("RIGHTPADDING",(0,0),(-1,-1), 12),
        ("BOX", (0,0),(-1,-1), 1, C_GREEN),
        ("ALIGN", (0,1),(0,1), "CENTER"),
    ]))
    return t

def drug_table(headers, rows, col_widths=None):
    if col_widths is None:
        col_widths = [body_w/len(headers)]*len(headers)
    data = [[Paragraph(h, S("Normal", fontName="Helvetica-Bold", fontSize=9, textColor=C_WHITE)) for h in headers]]
    for row in rows:
        data.append([Paragraph(str(c), S("Normal", fontSize=9, leading=12)) for c in row])
    t = Table(data, colWidths=col_widths, repeatRows=1)
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,0), C_DARK_BLUE),
        ("ROWBACKGROUNDS", (0,1), (-1,-1), [C_WHITE, C_GREY_BG]),
        ("GRID", (0,0), (-1,-1), 0.4, C_GREY_LINE),
        ("TOPPADDING",  (0,0),(-1,-1), 5),
        ("BOTTOMPADDING",(0,0),(-1,-1), 5),
        ("LEFTPADDING", (0,0),(-1,-1), 7),
        ("RIGHTPADDING",(0,0),(-1,-1), 7),
        ("VALIGN", (0,0),(-1,-1), "TOP"),
    ]))
    return t

def br(n=1):
    return Spacer(1, n*0.3*cm)

def hr():
    return HRFlowable(width="100%", thickness=0.5, color=C_GREY_LINE, spaceAfter=4, spaceBefore=4)

# ═══════════════════════════════════════════════════════════════════════════
# Build story
# ═══════════════════════════════════════════════════════════════════════════
story = []

# ── COVER PAGE ───────────────────────────────────────────────────────────────
# Full-page blue rectangle simulated via a table
cover_data = [[Paragraph("PHARMACOLOGY", cover_title)],
              [Paragraph("STUDY GUIDE", cover_title)],
              [Spacer(1, 0.6*cm)],
              [Paragraph("Exam Preparation | Key Points | Structures | Tables", cover_sub)],
              [Spacer(1, 0.4*cm)],
              [Paragraph("Routes of Drug Administration  •  Bioavailability  •  Cholinergic Drugs  •  Glaucoma", cover_sub)],
              [Spacer(1, 1.2*cm)],
              [Paragraph("Based on: Lippincott | Ganong | Katzung | Goodman & Gilman | Wills Eye Manual", cover_by)],
             ]
cover_t = Table(cover_data, colWidths=[body_w])
cover_t.setStyle(TableStyle([
    ("BACKGROUND", (0,0),(-1,-1), C_DARK_BLUE),
    ("TOPPADDING", (0,0),(-1,-1), 10),
    ("BOTTOMPADDING",(0,0),(-1,-1), 10),
    ("LEFTPADDING", (0,0),(-1,-1), 20),
    ("RIGHTPADDING",(0,0),(-1,-1), 20),
    ("BOX", (0,0),(-1,-1), 0, C_DARK_BLUE),
]))
story.append(Spacer(1, 3*cm))
story.append(cover_t)
story.append(PageBreak())

# ── TABLE OF CONTENTS ────────────────────────────────────────────────────────
story.append(section_banner("TABLE OF CONTENTS", C_MED_BLUE))
story.append(br())
toc_items = [
    ("1", "Routes of Drug Administration", "3"),
    ("2", "Bioavailability – Definition & Factors", "5"),
    ("3", "Cholinergic Drugs – Classification & Actions of ACh", "7"),
    ("4", "Drugs Used in Glaucoma", "10"),
]
toc_data = []
for num, topic, pg in toc_items:
    toc_data.append([
        Paragraph(num, toc_num),
        Paragraph(topic, toc_style),
        Paragraph(f"Pg {pg}", S("Normal", fontName="Helvetica-Bold", fontSize=10, textColor=C_MED_BLUE, alignment=TA_CENTER)),
    ])
toc_t = Table(toc_data, colWidths=[1*cm, body_w-3*cm, 2*cm])
toc_t.setStyle(TableStyle([
    ("ROWBACKGROUNDS",(0,0),(-1,-1),[C_WHITE, C_GREY_BG]),
    ("GRID", (0,0),(-1,-1), 0.3, C_GREY_LINE),
    ("TOPPADDING",(0,0),(-1,-1),8),
    ("BOTTOMPADDING",(0,0),(-1,-1),8),
    ("LEFTPADDING",(0,0),(-1,-1),10),
    ("RIGHTPADDING",(0,0),(-1,-1),10),
    ("VALIGN",(0,0),(-1,-1),"MIDDLE"),
]))
story.append(toc_t)
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════════════════
# SECTION 1 – ROUTES OF DRUG ADMINISTRATION
# ═══════════════════════════════════════════════════════════════════════════
story.append(section_banner("SECTION 1   ROUTES OF DRUG ADMINISTRATION", C_DARK_BLUE, num=""))
story.append(br())
story.append(Paragraph(
    "The route of administration is chosen based on the drug's properties (lipid/water solubility, stability) "
    "and therapeutic goals (speed of onset, site of action, duration). Three major categories: Enteral, Parenteral, Other.",
    body))
story.append(br())

# ── 1A. Enteral ──────────────────────────────────────────────────────────────
story.append(Paragraph("A.  ENTERAL ROUTES  (via GI tract)", h2))
story.append(hr())

enteral_data = [
    ["Route", "How?", "Advantages", "Disadvantages / Notes"],
    ["Oral (PO)", "Swallowed; absorbed in stomach/intestine",
     "Most convenient; self-administered; large range of formulations; overdose managed with activated charcoal",
     "First-pass metabolism ↓ bioavailability; gastric pH inactivates acid-labile drugs; slow onset; N/A in unconscious patients"],
    ["Sublingual", "Placed under tongue",
     "Rapid absorption; bypasses GI; avoids first-pass metabolism",
     "Limited drug volume; must not swallow saliva immediately"],
    ["Buccal", "Between cheek and gum",
     "Same as sublingual; useful for sustained local delivery",
     "Saliva can wash drug away"],
]
story.append(drug_table(
    enteral_data[0], enteral_data[1:],
    col_widths=[2.2*cm, 3.5*cm, 5.5*cm, 5.8*cm]
))
story.append(br())
story.append(Paragraph("<b>Special Oral Formulations:</b>", h3))
story.append(Paragraph("• <b>Enteric-coated:</b> Resists stomach acid; dissolves in alkaline intestine. Used for acid-labile drugs (omeprazole) or gastric irritants (aspirin).", bullet))
story.append(Paragraph("• <b>Extended-release (ER/SR/XR/CR):</b> Slow drug release → prolonged action, fewer doses/day, better compliance, reduces peak-trough fluctuations. E.g., morphine ER: 2 doses/day vs 6 for immediate-release.", bullet))
story.append(br())

# ── 1B. Parenteral ──────────────────────────────────────────────────────────
story.append(Paragraph("B.  PARENTERAL ROUTES  (bypasses GI tract)", h2))
story.append(hr())
story.append(Paragraph(
    "Used for: drugs poorly absorbed/unstable in GI (heparin, insulin), unconscious patients, and when rapid onset is needed. "
    "<b>Irreversible</b> once administered. Risks: pain, infection, local tissue damage.",
    body))
story.append(br())

par_data = [
    ["Route", "Speed", "Key Features", "Example"],
    ["Intravenous (IV)", "Fastest (seconds)", "100% bioavailability; bolus = immediate peak; infusion = sustained level; most control over dose", "Rocuronium, vancomycin, chemotherapy"],
    ["Intramuscular (IM)", "Minutes", "Aqueous solutions: rapid; Depot (oil/PEG): slow, sustained release", "Vaccines, depot antipsychotics (haloperidol decanoate)"],
    ["Subcutaneous (SC)", "Slow", "Constant absorption; avoids hemolysis/thrombosis; do NOT use irritating drugs (necrosis)", "Insulin, heparin, epinephrine auto-injector"],
    ["Intradermal (ID)", "Very slow / local", "Injection into dermis; mainly for diagnostics", "Tuberculin skin test, allergy testing"],
]
story.append(drug_table(
    par_data[0], par_data[1:],
    col_widths=[3.2*cm, 2.8*cm, 6*cm, 5*cm]
))
story.append(br())

# ── 1C. Other routes ────────────────────────────────────────────────────────
story.append(Paragraph("C.  OTHER ROUTES", h2))
story.append(hr())
other_data = [
    ["Route", "Onset", "Key Use / Features"],
    ["Inhalation", "Rapid (near IV)", "Gases + aerosols; direct lung delivery (asthma, COPD); minimises systemic SE"],
    ["Nasal", "Rapid", "Systemic or local; allergic rhinitis, desmopressin, nasal vaccines"],
    ["Intrathecal / Intraventricular", "Rapid (CNS)", "Bypasses blood-brain barrier; spinal anaesthesia, CNS infections, intrathecal chemo"],
    ["Transdermal patch", "Slow / sustained", "Avoids first-pass; prolonged systemic delivery; nitroglycerin, fentanyl, nicotine patch"],
    ["Rectal (PR)", "Variable", "Useful when oral route unavailable (vomiting, unconscious); partial avoidance of first-pass"],
    ["Topical", "Minimal systemic", "Local skin/mucosa effect; corticosteroid creams, antifungal"],
]
story.append(drug_table(
    other_data[0], other_data[1:],
    col_widths=[4.2*cm, 3*cm, 10*cm]
))
story.append(br())
story.append(key_point_box(
    "First-pass metabolism is avoided by: sublingual, buccal, IV, SC, IM, inhalation, transdermal, and rectal routes. "
    "Only oral (swallowed) and to some extent rectal routes undergo significant first-pass effect."
))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════════════════
# SECTION 2 – BIOAVAILABILITY
# ═══════════════════════════════════════════════════════════════════════════
story.append(section_banner("SECTION 2   BIOAVAILABILITY", C_DARK_BLUE))
story.append(br())

story.append(Paragraph("DEFINITION", h2))
story.append(hr())
story.append(Paragraph(
    "<b>Bioavailability (F)</b> is the rate and extent to which an administered drug reaches the "
    "<b>systemic circulation in an unchanged (active) form</b>. It is expressed as a fraction (0–1) or percentage.",
    body))
story.append(br())

defn_data = [
    ["Formula", "F  =  AUC(route) ÷ AUC(IV)  ×  100%"],
    ["IV reference", "100% bioavailability (gold standard)"],
    ["Example", "100 mg oral dose → 70 mg reaches circulation unchanged → F = 70%"],
    ["Measurement", "Plot plasma concentration vs. time → calculate Area Under Curve (AUC)"],
]
def_t = Table(defn_data, colWidths=[4*cm, body_w-4*cm])
def_t.setStyle(TableStyle([
    ("ROWBACKGROUNDS",(0,0),(-1,-1),[C_LIGHT_BLUE, C_WHITE]),
    ("GRID",(0,0),(-1,-1),0.4,C_GREY_LINE),
    ("FONTNAME",(0,0),(0,-1),"Helvetica-Bold"),
    ("FONTSIZE",(0,0),(-1,-1),9.5),
    ("TOPPADDING",(0,0),(-1,-1),6),
    ("BOTTOMPADDING",(0,0),(-1,-1),6),
    ("LEFTPADDING",(0,0),(-1,-1),10),
    ("RIGHTPADDING",(0,0),(-1,-1),10),
]))
story.append(def_t)
story.append(br(2))

story.append(Paragraph("FACTORS AFFECTING BIOAVAILABILITY", h2))
story.append(hr())

factors = [
    ("1. First-Pass Hepatic Metabolism ★ MOST IMPORTANT", C_RED, C_RED_LIGHT,
     ["Oral drugs enter the portal circulation → liver → if rapidly metabolised, less unchanged drug reaches systemic circulation.",
      "Examples: Nitroglycerin >90% cleared → given sublingually/transdermally/IV; lidocaine, propranolol also high first-pass.",
      "Solution: Use higher oral doses, or use an alternative route."]),
    ("2. Drug Solubility", C_MED_BLUE, C_LIGHT_BLUE,
     ["Very hydrophilic: cannot cross lipid cell membranes → poor absorption.",
      "Very lipophilic: insoluble in aqueous body fluids → cannot reach cell surface → also poor absorption.",
      "Ideal drug: mostly lipophilic with some aqueous solubility. That is why many drugs are weak acids or weak bases."]),
    ("3. Chemical Instability", C_GREEN, C_GREEN_LIGHT,
     ["Acid lability: Penicillin G destroyed by gastric pH.",
      "Enzymatic degradation: Insulin broken down by GI proteases.",
      "Solution: Use acid-resistant formulations, or parenteral route."]),
    ("4. Drug Formulation", C_PURPLE, C_PURPLE_LIGHT,
     ["Particle size, salt form, crystal structure, excipients → affect dissolution rate.",
      "Enteric coatings, ER systems, prodrugs, nanoparticle carriers all alter absorption.",
      "Generic vs branded: different formulations may give different bioavailability (bioequivalence testing required)."]),
    ("5. GI Motility", C_MED_BLUE, C_LIGHT_BLUE,
     ["Faster gastric emptying → drug reaches small intestine sooner → faster absorption.",
      "Slower motility (opioids, anticholinergics) → delayed absorption.",
      "Diarrhoea → too fast transit → reduced absorption."]),
    ("6. Drug Interactions in the GI Tract", C_RED, C_RED_LIGHT,
     ["Chelation: Antacids (Ca²⁺, Mg²⁺, Al³⁺) bind tetracyclines/fluoroquinolones → ↓ absorption.",
      "P-glycoprotein (P-gp) efflux pumps in gut wall: actively pump drugs back into intestinal lumen → ↓ bioavailability.",
      "CYP3A4 inhibitors (grapefruit juice): ↑ bioavailability of CYP3A4 substrates."]),
    ("7. Food and Gastric pH", C_GREEN, C_GREEN_LIGHT,
     ["Food: delays absorption for some drugs (e.g., antibiotics); enhances for others (e.g., fat-soluble drugs with fatty meals).",
      "pH alters drug ionisation: unionised form = lipophilic = better absorbed.",
      "Weak acid drugs (e.g., aspirin): better absorbed in acidic stomach.",
      "Weak base drugs (e.g., morphine): better absorbed in alkaline intestine."]),
    ("8. Presystemic Gut Wall Metabolism", C_PURPLE, C_PURPLE_LIGHT,
     ["CYP3A4 in intestinal enterocytes metabolises some drugs before absorption (contributes to first-pass effect).",
      "Example: cyclosporine, midazolam extensively metabolised in gut wall."]),
]

for title, t_color, bg_color, bullets in factors:
    rows = [[Paragraph(title, S("Normal", fontName="Helvetica-Bold", fontSize=10, textColor=C_WHITE))]]
    for b in bullets:
        rows.append([Paragraph("• " + b, S("Normal", fontSize=9.5, leading=13))])
    ft = Table(rows, colWidths=[body_w])
    ft.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(0,0), t_color),
        ("BACKGROUND",(0,1),(-1,-1), bg_color),
        ("TOPPADDING",(0,0),(-1,-1),5),
        ("BOTTOMPADDING",(0,0),(-1,-1),5),
        ("LEFTPADDING",(0,0),(-1,-1),10),
        ("RIGHTPADDING",(0,0),(-1,-1),10),
        ("BOX",(0,0),(-1,-1),0.6,t_color),
    ]))
    story.append(ft)
    story.append(br(0.5))

story.append(br())
story.append(key_point_box(
    "F = 1 (100%) for IV only. First-pass metabolism is the single biggest reason oral bioavailability is less than 100%. "
    "Drugs with F < 10% orally (e.g., nitroglycerin, morphine at very high doses) must be given via alternative routes."
))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════════════════
# SECTION 3 – CHOLINERGIC DRUGS
# ═══════════════════════════════════════════════════════════════════════════
story.append(section_banner("SECTION 3   CHOLINERGIC DRUGS", C_DARK_BLUE))
story.append(br())

story.append(Paragraph("DEFINITION", h2))
story.append(hr())
story.append(Paragraph(
    "<b>Cholinergic drugs</b> (Parasympathomimetics) are agents that mimic, enhance, or block the actions of "
    "<b>acetylcholine (ACh)</b> at cholinergic receptors (muscarinic or nicotinic).",
    body))
story.append(br())

story.append(Paragraph("CLASSIFICATION OF CHOLINERGIC DRUGS", h2))
story.append(hr())

# Classification tree table
story.append(Paragraph("I. CHOLINERGIC AGONISTS (Parasympathomimetics)", h3))
story.append(Paragraph("<b>A. Direct-Acting – Choline Esters</b>", bullet_b))

ce_data = [
    ["Drug", "Receptor", "Stability", "Clinical Use"],
    ["Acetylcholine (ACh)", "Muscarinic + Nicotinic", "Rapidly hydrolysed", "Ophthalmic miosis post-surgery"],
    ["Methacholine", "Mainly Muscarinic", "More stable", "Bronchial provocation test (asthma dx)"],
    ["Carbachol", "Muscarinic + Nicotinic", "Resistant to cholinesterase", "Glaucoma, intraocular miosis"],
    ["Bethanechol", "Muscarinic (M3)", "Resistant to cholinesterase", "Urinary retention, postop ileus"],
]
story.append(drug_table(ce_data[0], ce_data[1:], col_widths=[3.8*cm, 3.8*cm, 3.8*cm, 5.6*cm]))
story.append(br(0.5))

story.append(Paragraph("<b>B. Direct-Acting – Alkaloids (Natural)</b>", bullet_b))
alk_data = [
    ["Drug", "Receptor", "Clinical Use"],
    ["Pilocarpine", "Muscarinic", "Glaucoma (↑ outflow), Sjögren syndrome (xerostomia)"],
    ["Muscarine", "Muscarinic", "Toxic (toadstool poisoning) — reference compound"],
    ["Nicotine", "Nicotinic", "Smoking cessation (patches, gum)"],
]
story.append(drug_table(alk_data[0], alk_data[1:], col_widths=[3.5*cm, 3.5*cm, 10*cm]))
story.append(br(0.8))

story.append(Paragraph("II. INDIRECT-ACTING CHOLINERGIC AGONISTS (Anticholinesterases)", h3))
story.append(Paragraph("These inhibit acetylcholinesterase → ↑ ACh in synapse → prolonged/enhanced cholinergic effect.", body))
story.append(br(0.5))
story.append(Paragraph("<b>A. Reversible Inhibitors</b>", bullet_b))

rev_data = [
    ["Drug", "Duration", "Key Use"],
    ["Edrophonium", "Very short (5 min)", "Diagnosis of myasthenia gravis (Tensilon test)"],
    ["Physostigmine", "Short; crosses BBB", "Antidote for anticholinergic toxicity (atropine OD)"],
    ["Neostigmine", "Intermediate; does NOT cross BBB", "Reversal of NMB; myasthenia gravis"],
    ["Pyridostigmine", "Longer", "Myasthenia gravis (drug of choice)"],
    ["Donepezil", "Long; CNS-selective", "Alzheimer's disease (mild to moderate)"],
    ["Rivastigmine", "Long; CNS-selective", "Alzheimer's disease, Parkinson's dementia"],
    ["Galantamine", "Long; CNS-selective", "Alzheimer's disease"],
]
story.append(drug_table(rev_data[0], rev_data[1:], col_widths=[3.5*cm, 5*cm, 8.5*cm]))
story.append(br(0.5))

story.append(Paragraph("<b>B. Irreversible Inhibitors (Organophosphates)</b>", bullet_b))
irr_data = [
    ["Drug", "Use / Context"],
    ["Echothiophate", "Ophthalmic — glaucoma (rarely used now)"],
    ["Malathion, Parathion", "Insecticides/pesticides — causes poisoning"],
    ["Sarin, Tabun", "Chemical warfare nerve agents — mass casualties"],
]
story.append(drug_table(irr_data[0], irr_data[1:], col_widths=[5*cm, body_w-5*cm]))
story.append(br(0.5))
story.append(mnemonic_box("SLUDGE  (Organophosphate Poisoning)",
    ["S – Salivation", "L – Lacrimation", "U – Urination",
     "D – Defecation", "G – GI cramps", "E – Emesis / Eyes (miosis)"]))
story.append(br(0.5))

story.append(Paragraph("III. CHOLINERGIC ANTAGONISTS (Anticholinergics / Antimuscarinics)", h3))
story.append(Paragraph(
    "Block muscarinic or nicotinic receptors. Examples: Atropine (muscarinic antagonist, prototype), "
    "scopolamine, ipratropium, tiotropium, tubocurarine (NMJ blocker).",
    body))
story.append(br())

story.append(Paragraph("ACTIONS OF ACETYLCHOLINE (ACh)", h2))
story.append(hr())
story.append(Paragraph("ACh acts at two receptor families:", body))
story.append(br(0.5))

# Receptor structure summary
rec_data = [
    ["Receptor Type", "Location", "Signal Mechanism", "Blocked By"],
    ["Muscarinic (M1-M5)", "Smooth muscle, glands, heart, CNS, ganglia (M1)", "GPCR: Gq/Gi/Go → IP3, DAG, Ca²⁺ or ↓cAMP or K⁺ channel opening", "Atropine"],
    ["Nicotinic-M (NM)", "Neuromuscular junction (skeletal muscle)", "Ligand-gated ion channel → Na⁺ influx → depolarisation → muscle contraction", "Tubocurarine (d-tubocurarine)"],
    ["Nicotinic-N (NN)", "Autonomic ganglia, CNS, adrenal medulla", "Ligand-gated ion channel; high Ca²⁺ permeability", "Hexamethonium"],
]
story.append(drug_table(rec_data[0], rec_data[1:],
    col_widths=[3.5*cm, 3.8*cm, 7*cm, 3*cm]))
story.append(br())

# Muscarinic effects by organ
story.append(Paragraph("Muscarinic Effects by Organ System", h3))
musc_data = [
    ["Organ", "Muscarinic Effect", "Receptor"],
    ["Eye – pupil", "Miosis (sphincter contraction)", "M3"],
    ["Eye – ciliary muscle", "Contraction → near vision / accommodation", "M3"],
    ["Heart (SA node)", "↓ Heart rate (bradycardia)", "M2"],
    ["Heart (AV node)", "↓ Conduction velocity", "M2"],
    ["Blood vessels", "Vasodilation (via endothelial NO release)", "M3"],
    ["Bronchi", "Bronchoconstriction + ↑ secretions", "M3"],
    ["GI tract", "↑ Motility + secretions; sphincter relaxation", "M2/M3"],
    ["Urinary bladder", "Detrusor contraction (voiding); sphincter relaxation", "M3"],
    ["Glands (salivary, lacrimal, sweat)", "↑ Secretion", "M3"],
]
story.append(drug_table(musc_data[0], musc_data[1:],
    col_widths=[5.5*cm, 8.5*cm, 3*cm]))
story.append(br(0.5))
story.append(mnemonic_box("DUMBELS  (Muscarinic/Cholinergic Excess)",
    ["D – Defecation / Diarrhoea",
     "U – Urination (incontinence)",
     "M – Miosis",
     "B – Bradycardia / Bronchospasm",
     "E – Emesis",
     "L – Lacrimation",
     "S – Salivation / Sweating"]))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════════════════
# SECTION 4 – DRUGS USED IN GLAUCOMA
# ═══════════════════════════════════════════════════════════════════════════
story.append(section_banner("SECTION 4   DRUGS USED IN GLAUCOMA  (5 Marks)", C_DARK_BLUE))
story.append(br())

story.append(Paragraph("BACKGROUND", h2))
story.append(hr())
story.append(Paragraph(
    "Glaucoma is elevated intraocular pressure (IOP) that damages the optic nerve → irreversible vision loss. "
    "Almost all elevated IOP is caused by <b>obstruction to aqueous humor outflow</b>. "
    "Aqueous humor is produced by the ciliary body, flows through the anterior chamber, and drains via the "
    "<b>trabecular meshwork → Canal of Schlemm</b>.",
    body))
story.append(br(0.5))

# Two mechanisms
mech_data = [
    ["Mechanism of IOP Reduction", "Drug Classes"],
    ["↓ Aqueous humor production", "Beta-blockers, Carbonic anhydrase inhibitors (CAIs), Alpha-2 agonists"],
    ["↑ Aqueous humor outflow", "Prostaglandin analogs (↑ uveoscleral outflow), Miotics/Pilocarpine (↑ trabecular outflow), Alpha-2 agonists"],
    ["Emergency IOP reduction", "Osmotic agents (mannitol), Systemic CAIs (acetazolamide)"],
]
mt = Table(mech_data, colWidths=[6*cm, body_w-6*cm])
mt.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,0), C_MED_BLUE),
    ("FONTNAME",(0,0),(-1,0),"Helvetica-Bold"),
    ("FONTSIZE",(0,0),(-1,-1),9.5),
    ("TEXTCOLOR",(0,0),(-1,0), C_WHITE),
    ("ROWBACKGROUNDS",(0,1),(-1,-1),[C_LIGHT_BLUE, C_WHITE]),
    ("GRID",(0,0),(-1,-1),0.4,C_GREY_LINE),
    ("TOPPADDING",(0,0),(-1,-1),6),
    ("BOTTOMPADDING",(0,0),(-1,-1),6),
    ("LEFTPADDING",(0,0),(-1,-1),10),
    ("RIGHTPADDING",(0,0),(-1,-1),10),
    ("VALIGN",(0,0),(-1,-1),"TOP"),
]))
story.append(mt)
story.append(br())

# Each drug class
glaucoma_drugs = [
    {
        "title": "1. BETA-BLOCKERS  (↓ Aqueous Production)",
        "color": C_MED_BLUE,
        "bg": C_LIGHT_BLUE,
        "drugs": "Timolol (0.25%, 0.5%)  |  Betaxolol (cardioselective)  |  Levobunolol  |  Carteolol",
        "mech": "Block β₂ receptors on ciliary epithelium → ↓ aqueous humor secretion",
        "use": "Open-angle glaucoma (first-line); applied twice daily",
        "se": "Bradycardia, bronchospasm, depression, fatigue",
        "ci": "Asthma, COPD, heart block, bradycardia. Use betaxolol (β₁ selective) if respiratory disease",
    },
    {
        "title": "2. PROSTAGLANDIN ANALOGS  (↑ Uveoscleral Outflow)  ★ Most Effective",
        "color": C_GREEN,
        "bg": C_GREEN_LIGHT,
        "drugs": "Latanoprost (0.005%)  |  Bimatoprost  |  Travoprost  |  Tafluprost",
        "mech": "Stimulate FP prostaglandin receptors → ↑ uveoscleral outflow of aqueous humor",
        "use": "First-line for most types of glaucoma; once daily at night (greatest IOP reduction at night)",
        "se": "Conjunctival hyperemia, iris colour change (increased pigmentation), eyelash growth (hypertrichosis), periorbital fat atrophy",
        "ci": "Relative caution in uveitis, pregnancy",
    },
    {
        "title": "3. ALPHA-2 AGONISTS  (↓ Production + ↑ Outflow)",
        "color": C_PURPLE,
        "bg": C_PURPLE_LIGHT,
        "drugs": "Brimonidine (0.1%, 0.15%, 0.2%)  |  Apraclonidine",
        "mech": "Stimulate α₂ adrenergic receptors → ↓ aqueous production + ↑ uveoscleral outflow; brimonidine also has neuroprotective properties",
        "use": "Adjunctive therapy; also for short-term prophylaxis against IOP spikes post-laser",
        "se": "Drowsiness, dry mouth, ocular allergy (apraclonidine > brimonidine)",
        "ci": "MAO inhibitor use (risk of hypertensive crisis); caution in children (CNS depression)",
    },
    {
        "title": "4. CARBONIC ANHYDRASE INHIBITORS – CAIs  (↓ Aqueous Production)",
        "color": C_ACCENT,
        "bg": C_ORANGE_LIGHT,
        "drugs": "Topical: Dorzolamide (2%), Brinzolamide (1%)  |  Systemic: Acetazolamide, Methazolamide",
        "mech": "Inhibit carbonic anhydrase in ciliary epithelium → ↓ HCO₃⁻ and Na⁺ transport → ↓ aqueous humor formation",
        "use": "Topical: adjunct therapy. Systemic acetazolamide: acute angle-closure glaucoma attack (IV/oral)",
        "se": "Topical: burning, bitter taste. Systemic: metabolic acidosis, hypokalemia, kidney stones, paresthesias ('sulfa drug' reaction), diuresis",
        "ci": "Sulfonamide allergy (cross-reactivity), renal failure",
    },
    {
        "title": "5. CHOLINERGIC AGONISTS / MIOTICS  (↑ Trabecular Outflow)",
        "color": C_RED,
        "bg": C_RED_LIGHT,
        "drugs": "Pilocarpine (1%, 2%, 4%)  |  Carbachol",
        "mech": "Muscarinic agonist → contracts ciliary muscle + sphincter pupillae → opens trabecular meshwork drainage → ↑ outflow; causes miosis",
        "use": "Open-angle glaucoma; acute angle-closure attack (rapid miosis opens drainage angle); applied 3–4× daily",
        "se": "Miosis (poor night vision), brow ache, myopia (ciliary muscle spasm), risk of retinal detachment (avoid in high myopes)",
        "ci": "Uveitis, active inflammation; retinal detachment risk",
    },
    {
        "title": "6. OSMOTIC AGENTS  (Emergency – ↓ Vitreous Volume)",
        "color": C_MED_BLUE,
        "bg": C_LIGHT_BLUE,
        "drugs": "Mannitol (IV, 20%)  |  Glycerin (oral)",
        "mech": "Create osmotic gradient → draw fluid from vitreous into blood → rapid ↓ IOP",
        "use": "Acute angle-closure glaucoma attack as emergency measure",
        "se": "Mannitol: volume overload, headache, electrolyte disturbance. Glycerin: hyperglycaemia (avoid in diabetes)",
        "ci": "Mannitol: anuria, CHF, pulmonary oedema",
    },
]

for drug in glaucoma_drugs:
    gd = [
        [Paragraph(drug["title"], S("Normal", fontName="Helvetica-Bold", fontSize=10.5, textColor=C_WHITE))],
        [Table([
            [Paragraph("<b>Drugs:</b>", S("Normal", fontName="Helvetica-Bold", fontSize=9.5)), Paragraph(drug["drugs"], body)],
            [Paragraph("<b>Mechanism:</b>", S("Normal", fontName="Helvetica-Bold", fontSize=9.5)), Paragraph(drug["mech"], body)],
            [Paragraph("<b>Clinical Use:</b>", S("Normal", fontName="Helvetica-Bold", fontSize=9.5)), Paragraph(drug["use"], body)],
            [Paragraph("<b>Side Effects:</b>", S("Normal", fontName="Helvetica-Bold", fontSize=9.5)), Paragraph(drug["se"], body)],
            [Paragraph("<b>Caution/CI:</b>", S("Normal", fontName="Helvetica-Bold", fontSize=9.5)), Paragraph(drug["ci"], body)],
        ], colWidths=[2.8*cm, body_w-2.8*cm-0.4*cm],
        style=[
            ("TOPPADDING",(0,0),(-1,-1),4),("BOTTOMPADDING",(0,0),(-1,-1),4),
            ("LEFTPADDING",(0,0),(-1,-1),6),("RIGHTPADDING",(0,0),(-1,-1),6),
            ("VALIGN",(0,0),(-1,-1),"TOP"),
        ])],
    ]
    gt = Table(gd, colWidths=[body_w])
    gt.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(-1,0), drug["color"]),
        ("BACKGROUND",(0,1),(-1,-1), drug["bg"]),
        ("BOX",(0,0),(-1,-1),0.8, drug["color"]),
        ("TOPPADDING",(0,0),(-1,0),7),("BOTTOMPADDING",(0,0),(-1,0),7),
        ("LEFTPADDING",(0,0),(-1,0),12),("RIGHTPADDING",(0,0),(-1,0),12),
        ("TOPPADDING",(0,1),(-1,-1),4),("BOTTOMPADDING",(0,1),(-1,-1),4),
        ("LEFTPADDING",(0,1),(-1,-1),4),("RIGHTPADDING",(0,1),(-1,-1),4),
    ]))
    story.append(KeepTogether([gt, Spacer(1, 0.3*cm)]))

story.append(br())

# Summary table
story.append(Paragraph("QUICK REFERENCE SUMMARY TABLE", h2))
story.append(hr())
summ_data = [
    ["Drug Class", "Example", "Mechanism", "Route", "IOP ↓"],
    ["Beta-blocker", "Timolol", "↓ Aqueous production", "Topical (eye drops)", "↓↓"],
    ["Prostaglandin analog", "Latanoprost", "↑ Uveoscleral outflow", "Topical (once daily)", "↓↓↓"],
    ["Alpha-2 agonist", "Brimonidine", "↓ Production + ↑ outflow", "Topical", "↓↓"],
    ["CAI – Topical", "Dorzolamide", "↓ Aqueous production", "Topical", "↓↓"],
    ["CAI – Systemic", "Acetazolamide", "↓ Aqueous production", "Oral / IV", "↓↓↓"],
    ["Miotic", "Pilocarpine", "↑ Trabecular outflow", "Topical (3–4×/day)", "↓↓"],
    ["Osmotic", "Mannitol", "↓ Vitreous volume", "IV (emergency)", "↓↓ (acute)"],
]
story.append(drug_table(
    summ_data[0], summ_data[1:],
    col_widths=[4*cm, 3.2*cm, 5.5*cm, 3.5*cm, 1.8*cm]
))
story.append(br(1.5))
story.append(key_point_box(
    "For acute angle-closure glaucoma: use ALL classes simultaneously — topical beta-blocker + alpha-2 agonist + pilocarpine + CAI + systemic acetazolamide ± IV mannitol. "
    "Prostglandin analogs are contraindicated in acute attack (they can worsen inflammation)."
))

# ── Back page ────────────────────────────────────────────────────────────────
story.append(PageBreak())
story.append(section_banner("EXAM QUICK-RECALL CARDS", C_MED_BLUE))
story.append(br())

cards = [
    ("Routes – Quick Memory", [
        "Enteral = via GI tract: Oral | Sublingual | Buccal",
        "Parenteral = bypasses GI: IV (fastest, 100% F) | IM | SC | ID",
        "Other: Inhalation | Nasal | Intrathecal | Transdermal | Rectal",
        "First-pass avoided by: ALL except oral (swallowed) and rectal",
    ], C_MED_BLUE, C_LIGHT_BLUE),
    ("Bioavailability – Quick Memory", [
        "F = AUC(route)/AUC(IV) × 100%  |  IV = 100% F",
        "Key factors: First-pass ★ | Solubility | Instability | Formulation | GI motility | Drug interactions | Food/pH",
        "High first-pass drugs: Nitroglycerin, Propranolol, Lidocaine, Morphine, Verapamil",
        "Mnemonic: FISH-F = First-pass, Instability, Solubility, Interactions, Food/pH, Formulation",
    ], C_GREEN, C_GREEN_LIGHT),
    ("Cholinergic – Quick Memory", [
        "Direct agonists: Bethanechol (urinary retention), Pilocarpine (glaucoma), Carbachol, Methacholine",
        "Indirect (AChE inhibitors): Neostigmine (MG/NMB reversal), Physostigmine (atropine OD), Donepezil (Alzheimer's)",
        "ACh muscarinic effects: DUMBELS  |  Nicotinic: depolarisation at NMJ + ganglia",
        "Receptors: M2 (heart), M3 (smooth muscle/glands), NM (muscle, blocked by curare), NN (ganglia, blocked by hexamethonium)",
    ], C_PURPLE, C_PURPLE_LIGHT),
    ("Glaucoma Drugs – Quick Memory", [
        "↓ Production: Beta-blockers (Timolol) | CAIs (Dorzolamide/Acetazolamide) | Alpha-2 agonists (Brimonidine)",
        "↑ Outflow: Prostaglandins (Latanoprost – once daily at night) | Miotics (Pilocarpine)",
        "Emergency: Mannitol IV | Acetazolamide IV | Pilocarpine (miosis opens angle)",
        "AVOID Prostaglandins in ACUTE angle-closure. AVOID beta-blockers in asthma/COPD/heart block.",
    ], C_RED, C_RED_LIGHT),
]

for title, points, tc, bc in cards:
    rows = [[Paragraph(title, S("Normal", fontName="Helvetica-Bold", fontSize=10.5, textColor=C_WHITE))]]
    for pt in points:
        rows.append([Paragraph("• " + pt, S("Normal", fontSize=9.5, leading=14))])
    ct = Table(rows, colWidths=[body_w])
    ct.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(0,0), tc),
        ("BACKGROUND",(0,1),(-1,-1), bc),
        ("BOX",(0,0),(-1,-1),0.8, tc),
        ("TOPPADDING",(0,0),(-1,-1),6),("BOTTOMPADDING",(0,0),(-1,-1),6),
        ("LEFTPADDING",(0,0),(-1,-1),12),("RIGHTPADDING",(0,0),(-1,-1),12),
    ]))
    story.append(ct)
    story.append(br(0.8))

# ── Build PDF ────────────────────────────────────────────────────────────────
OUT = "/tmp/workspace/pharmacology-study-guide/Pharmacology_Study_Guide.pdf"

doc = SimpleDocTemplate(
    OUT, pagesize=A4,
    leftMargin=MARGIN, rightMargin=MARGIN,
    topMargin=1.6*cm, bottomMargin=1.4*cm,
    title="Pharmacology Study Guide",
    author="Orris AI",
)
doc.build(story, onFirstPage=header_footer, onLaterPages=header_footer)
print(f"PDF created: {OUT}")