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 import BaseDocTemplate, Frame, PageTemplate
from reportlab.pdfgen import canvas
from reportlab.lib.colors import HexColor

OUTPUT = "/tmp/workspace/nanoemulsion-guide/Nanoemulsion_Characterization_Guide.pdf"

# ── Colour palette ──────────────────────────────────────────────────────────
NAVY    = HexColor("#1B3A6B")
TEAL    = HexColor("#1A8C8C")
LTBLUE  = HexColor("#D6EAF8")
LTGREY  = HexColor("#F4F6F7")
MIDGREY = HexColor("#BDC3C7")
WHITE   = colors.white
BLACK   = colors.black
ORANGE  = HexColor("#E67E22")
GREEN   = HexColor("#1E8449")

# ── Page layout ─────────────────────────────────────────────────────────────
PAGE_W, PAGE_H = A4
MARGIN = 2.0 * cm

def header_footer(canvas_obj, doc):
    canvas_obj.saveState()
    # Top bar
    canvas_obj.setFillColor(NAVY)
    canvas_obj.rect(0, PAGE_H - 1.2*cm, PAGE_W, 1.2*cm, fill=1, stroke=0)
    canvas_obj.setFillColor(WHITE)
    canvas_obj.setFont("Helvetica-Bold", 9)
    canvas_obj.drawString(MARGIN, PAGE_H - 0.8*cm,
                          "Nanoemulsion Characterization Guide")
    canvas_obj.setFont("Helvetica", 9)
    canvas_obj.drawRightString(PAGE_W - MARGIN, PAGE_H - 0.8*cm,
                               "Pharmaceutical Nanotechnology Reference")
    # Bottom bar
    canvas_obj.setFillColor(TEAL)
    canvas_obj.rect(0, 0, PAGE_W, 0.8*cm, fill=1, stroke=0)
    canvas_obj.setFillColor(WHITE)
    canvas_obj.setFont("Helvetica", 8)
    canvas_obj.drawCentredString(PAGE_W / 2, 0.25*cm, f"Page {doc.page}")
    canvas_obj.restoreState()

# ── Styles ───────────────────────────────────────────────────────────────────
base = getSampleStyleSheet()

def S(name, **kw):
    return ParagraphStyle(name, **kw)

style_cover_title = S("CoverTitle",
    fontSize=34, fontName="Helvetica-Bold",
    textColor=WHITE, alignment=TA_CENTER, leading=42, spaceAfter=8)

style_cover_sub = S("CoverSub",
    fontSize=16, fontName="Helvetica",
    textColor=LTBLUE, alignment=TA_CENTER, leading=22, spaceAfter=6)

style_cover_info = S("CoverInfo",
    fontSize=11, fontName="Helvetica",
    textColor=WHITE, alignment=TA_CENTER, leading=16)

style_h1 = S("H1",
    fontSize=18, fontName="Helvetica-Bold",
    textColor=NAVY, spaceBefore=14, spaceAfter=6, leading=22)

style_h2 = S("H2",
    fontSize=13, fontName="Helvetica-Bold",
    textColor=TEAL, spaceBefore=10, spaceAfter=4, leading=17)

style_h3 = S("H3",
    fontSize=11, fontName="Helvetica-Bold",
    textColor=NAVY, spaceBefore=8, spaceAfter=3, leading=14)

style_body = S("Body",
    fontSize=10, fontName="Helvetica",
    textColor=BLACK, leading=15, spaceAfter=5, alignment=TA_JUSTIFY)

style_bullet = S("Bullet",
    fontSize=10, fontName="Helvetica",
    textColor=BLACK, leading=14, spaceAfter=3,
    leftIndent=16, bulletIndent=6, firstLineIndent=0)

style_note = S("Note",
    fontSize=9, fontName="Helvetica-Oblique",
    textColor=HexColor("#555555"), leading=13, spaceAfter=4,
    leftIndent=10, rightIndent=10)

style_caption = S("Caption",
    fontSize=9, fontName="Helvetica-Bold",
    textColor=NAVY, alignment=TA_CENTER, spaceAfter=4)

style_toc_title = S("TOCTitle",
    fontSize=11, fontName="Helvetica",
    textColor=NAVY, leading=16, spaceAfter=2, leftIndent=8)

style_section_num = S("SecNum",
    fontSize=11, fontName="Helvetica-Bold",
    textColor=TEAL, leading=16, spaceAfter=2)

# ── Table helpers ─────────────────────────────────────────────────────────────
def cell(text, bold=False, color=BLACK, size=9, align=TA_LEFT):
    fn = "Helvetica-Bold" if bold else "Helvetica"
    st = ParagraphStyle("tc", fontSize=size, fontName=fn,
                        textColor=color, leading=13, alignment=align)
    return Paragraph(text, st)

def header_cell(text):
    return cell(text, bold=True, color=WHITE, size=9, align=TA_CENTER)

def make_table(headers, rows, col_widths, title=None):
    data = [[header_cell(h) for h in headers]]
    for row in rows:
        data.append([cell(str(v)) for v in row])
    t = Table(data, colWidths=col_widths, repeatRows=1)
    row_colors = []
    for i in range(1, len(data)):
        bg = LTGREY if i % 2 == 1 else WHITE
        row_colors.append(("BACKGROUND", (0, i), (-1, i), bg))
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0, 0), (-1, 0), NAVY),
        ("ROWBACKGROUNDS",(0, 1), (-1,-1), [LTGREY, WHITE]),
        ("GRID",          (0, 0), (-1,-1), 0.4, MIDGREY),
        ("TOPPADDING",    (0, 0), (-1,-1), 5),
        ("BOTTOMPADDING", (0, 0), (-1,-1), 5),
        ("LEFTPADDING",   (0, 0), (-1,-1), 6),
        ("RIGHTPADDING",  (0, 0), (-1,-1), 6),
        ("VALIGN",        (0, 0), (-1,-1), "MIDDLE"),
        ("ROWBACKGROUNDS",(0, 1), (-1,-1), [LTGREY, WHITE]),
    ] + row_colors))
    items = []
    if title:
        items.append(Paragraph(title, style_caption))
    items.append(t)
    return items

def section_box(number, title, story):
    """Render a coloured section header block."""
    story.append(Spacer(1, 0.3*cm))
    data = [[Paragraph(f"{number}", S("sn", fontSize=14,
                fontName="Helvetica-Bold", textColor=WHITE, leading=18)),
             Paragraph(title, S("st", fontSize=14,
                fontName="Helvetica-Bold", textColor=WHITE, leading=18))]]
    t = Table(data, colWidths=[1.0*cm, 14.6*cm])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0, 0), (-1, -1), NAVY),
        ("VALIGN",     (0, 0), (-1, -1), "MIDDLE"),
        ("LEFTPADDING",(0, 0), (-1, -1), 8),
        ("TOPPADDING", (0, 0), (-1, -1), 6),
        ("BOTTOMPADDING",(0,0),(-1,-1), 6),
    ]))
    story.append(t)
    story.append(Spacer(1, 0.2*cm))

def teal_bar(text, story):
    """Subsection teal bar."""
    data = [[Paragraph(text, S("tb", fontSize=11, fontName="Helvetica-Bold",
                               textColor=WHITE, leading=15))]]
    t = Table(data, colWidths=[15.6*cm])
    t.setStyle(TableStyle([
        ("BACKGROUND",   (0,0),(-1,-1), TEAL),
        ("LEFTPADDING",  (0,0),(-1,-1), 8),
        ("TOPPADDING",   (0,0),(-1,-1), 4),
        ("BOTTOMPADDING",(0,0),(-1,-1), 4),
    ]))
    story.append(Spacer(1, 0.15*cm))
    story.append(t)
    story.append(Spacer(1, 0.1*cm))

def bullet(text, story, indent=16):
    story.append(Paragraph(f"<bullet>&bull;</bullet> {text}", style_bullet))

def body(text, story):
    story.append(Paragraph(text, style_body))

def note(text, story):
    data = [[Paragraph(f"<b>NOTE:</b> {text}",
                       S("n2", fontSize=9, fontName="Helvetica-Oblique",
                         textColor=HexColor("#2C3E50"), leading=13))]]
    t = Table(data, colWidths=[15.6*cm])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),(-1,-1), HexColor("#EBF5FB")),
        ("LEFTPADDING",   (0,0),(-1,-1), 10),
        ("TOPPADDING",    (0,0),(-1,-1), 5),
        ("BOTTOMPADDING", (0,0),(-1,-1), 5),
        ("BOX",           (0,0),(-1,-1), 0.8, TEAL),
    ]))
    story.append(t)
    story.append(Spacer(1, 0.15*cm))

# ════════════════════════════════════════════════════════════════════════════
# BUILD DOCUMENT
# ════════════════════════════════════════════════════════════════════════════
def build_pdf():
    doc = BaseDocTemplate(
        OUTPUT, pagesize=A4,
        leftMargin=MARGIN, rightMargin=MARGIN,
        topMargin=1.6*cm, bottomMargin=1.4*cm,
        title="Nanoemulsion Characterization Guide",
        author="Pharmaceutical Nanotechnology Reference",
    )
    frame = Frame(MARGIN, 1.4*cm, PAGE_W - 2*MARGIN, PAGE_H - 3.2*cm,
                  id="main")
    doc.addPageTemplates([PageTemplate(id="main", frames=[frame],
                                       onPage=header_footer)])
    story = []

    # ── COVER PAGE ──────────────────────────────────────────────────────────
    # Full-page navy background via a big table
    cover_data = [[
        Paragraph("NANOEMULSION<br/>CHARACTERIZATION<br/>GUIDE", style_cover_title)
    ]]
    cover_t = Table(cover_data, colWidths=[15.6*cm],
                    rowHeights=[8*cm])
    cover_t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),(-1,-1), NAVY),
        ("VALIGN",        (0,0),(-1,-1), "MIDDLE"),
        ("TOPPADDING",    (0,0),(-1,-1), 30),
        ("BOTTOMPADDING", (0,0),(-1,-1), 30),
    ]))
    story.append(Spacer(1, 2*cm))
    story.append(cover_t)
    story.append(Spacer(1, 0.4*cm))

    sub_data = [[
        Paragraph("Techniques, Parameters & Acceptance Criteria<br/>"
                  "for Pharmaceutical Nanotechnology", style_cover_sub)
    ]]
    sub_t = Table(sub_data, colWidths=[15.6*cm], rowHeights=[2.5*cm])
    sub_t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),(-1,-1), TEAL),
        ("VALIGN",        (0,0),(-1,-1), "MIDDLE"),
        ("TOPPADDING",    (0,0),(-1,-1), 12),
        ("BOTTOMPADDING", (0,0),(-1,-1), 12),
    ]))
    story.append(sub_t)
    story.append(Spacer(1, 1*cm))

    info_data = [[
        Paragraph("Covers: Physical &bull; Chemical &bull; Thermodynamic &bull; "
                  "Biological &bull; Stability Characterization<br/>"
                  "Reference for Pharmaceutical Scientists and Researchers",
                  style_cover_info)
    ]]
    info_t = Table(info_data, colWidths=[15.6*cm])
    info_t.setStyle(TableStyle([
        ("BACKGROUND",   (0,0),(-1,-1), HexColor("#2E4057")),
        ("LEFTPADDING",  (0,0),(-1,-1), 16),
        ("TOPPADDING",   (0,0),(-1,-1), 10),
        ("BOTTOMPADDING",(0,0),(-1,-1), 10),
    ]))
    story.append(info_t)
    story.append(PageBreak())

    # ── TABLE OF CONTENTS ──────────────────────────────────────────────────
    story.append(Paragraph("Table of Contents", style_h1))
    story.append(HRFlowable(width="100%", thickness=2, color=TEAL,
                             spaceAfter=8))
    toc_items = [
        ("1", "Introduction to Nanoemulsions", 3),
        ("2", "Physical Characterization Techniques", 4),
        ("  2.1", "Droplet Size & Size Distribution (DLS)", 4),
        ("  2.2", "Zeta Potential", 5),
        ("  2.3", "Polydispersity Index (PDI)", 5),
        ("  2.4", "Viscosity & Rheology", 5),
        ("  2.5", "Refractive Index & Transmittance", 6),
        ("3", "Chemical Characterization Techniques", 6),
        ("  3.1", "Drug Content & Encapsulation Efficiency", 6),
        ("  3.2", "FTIR Spectroscopy", 7),
        ("  3.3", "DSC – Thermal Analysis", 7),
        ("  3.4", "pH Measurement", 7),
        ("  3.5", "Conductivity", 8),
        ("4", "Morphological Characterization", 8),
        ("  4.1", "Transmission Electron Microscopy (TEM)", 8),
        ("  4.2", "Scanning Electron Microscopy (SEM)", 8),
        ("  4.3", "Atomic Force Microscopy (AFM)", 9),
        ("5", "Stability Characterization", 9),
        ("  5.1", "Thermodynamic Stability Tests", 9),
        ("  5.2", "Physical Stability (Long-term Storage)", 10),
        ("  5.3", "Accelerated Stability (ICH Guidelines)", 10),
        ("6", "In Vitro Performance Testing", 10),
        ("  6.1", "Drug Release Studies (Franz Diffusion Cell)", 10),
        ("  6.2", "Ex Vivo Skin Permeation", 11),
        ("  6.3", "Antimicrobial / Antifungal Activity (MIC)", 11),
        ("7", "Biocompatibility & Safety Tests", 12),
        ("  7.1", "Cytotoxicity – MTT Assay", 12),
        ("  7.2", "Skin Irritation – HET-CAM / Draize Test", 12),
        ("8", "Acceptance Criteria Summary Table", 12),
        ("9", "Troubleshooting Guide", 13),
        ("10", "Key References", 14),
    ]
    for num, title, _ in toc_items:
        dot_line = "." * max(2, 60 - len(num) - len(title))
        toc_text = (f"<font name='Helvetica-Bold' color='#1B3A6B'>{num}</font>"
                    f"&nbsp;&nbsp;{title}"
                    f"<font color='#BDC3C7'> {dot_line} </font>")
        story.append(Paragraph(toc_text, style_toc_title))
    story.append(PageBreak())

    # ── SECTION 1: INTRODUCTION ─────────────────────────────────────────────
    section_box("1", "Introduction to Nanoemulsions", story)
    body("Nanoemulsions (NEs) are thermodynamically or kinetically stable colloidal "
         "dispersions of two immiscible liquids (typically oil-in-water or water-in-oil), "
         "with droplet diameters in the range of <b>20–500 nm</b>. Their nanoscale droplet "
         "size imparts unique physicochemical properties that make them superior carriers "
         "for pharmaceutical, cosmetic, and nutraceutical applications.", story)
    body("Unlike macroemulsions, NEs exhibit markedly enhanced drug solubilization, "
         "skin penetration, bioavailability, and physical stability. They appear "
         "translucent to transparent due to the small droplet size relative to the "
         "wavelength of visible light.", story)
    teal_bar("Key Advantages of Nanoemulsions", story)
    for adv in [
        "<b>Enhanced solubility</b> – Dramatically improves solubility of BCS Class II/IV drugs",
        "<b>Increased bioavailability</b> – Greater surface area facilitates faster drug absorption",
        "<b>Improved skin permeation</b> – Nanosized droplets penetrate stratum corneum more effectively",
        "<b>Sustained release</b> – Controlled drug release profiles reduce dosing frequency",
        "<b>Thermodynamic stability</b> – Resistance to creaming, flocculation, and phase separation",
        "<b>Versatility</b> – Can be formulated as liquids, gels, creams, sprays, or incorporated into dressings",
    ]:
        bullet(adv, story)
    story.append(Spacer(1, 0.2*cm))
    teal_bar("Classification by Droplet Size", story)
    rows = [
        ["Nanoemulsion",   "20–500 nm",   "Translucent/bluish", "Kinetically stable",
         "High-energy or low-energy methods"],
        ["Microemulsion",  "10–100 nm",   "Transparent",        "Thermodynamically stable",
         "Low-energy self-emulsification"],
        ["Macroemulsion",  ">1 µm",       "Opaque/milky",       "Unstable (separates)",
         "Simple mixing/homogenization"],
    ]
    headers = ["Type", "Droplet Size", "Appearance", "Stability", "Preparation"]
    widths = [2.8*cm, 2.5*cm, 3.0*cm, 3.2*cm, 4.1*cm]
    story.extend(make_table(headers, rows, widths,
                            "Table 1: Comparison of emulsion types"))
    story.append(PageBreak())

    # ── SECTION 2: PHYSICAL CHARACTERIZATION ────────────────────────────────
    section_box("2", "Physical Characterization Techniques", story)

    teal_bar("2.1  Droplet Size & Size Distribution – Dynamic Light Scattering (DLS)", story)
    body("<b>Principle:</b> DLS measures the Brownian motion of droplets in suspension. "
         "Fluctuations in scattered laser light intensity are used to calculate the "
         "hydrodynamic diameter via the Stokes-Einstein equation: "
         "<i>d = kT / (3πηD)</i>, where D is the diffusion coefficient, η is viscosity, "
         "and T is temperature.", story)
    body("<b>Instrument:</b> Zetasizer Nano ZS (Malvern Instruments) or equivalent. "
         "Sample diluted 1:100 in deionized water; measured at 25°C, 173° backscatter, "
         "in triplicate.", story)
    for p in [
        "<b>Z-average (hydrodynamic diameter):</b> Target &lt; 200 nm for topical NEs; &lt; 100 nm optimal",
        "<b>Intensity-weighted mean diameter:</b> Most sensitive to large particles/aggregates",
        "<b>Number-weighted mean:</b> Reflects true population average",
        "<b>Volume-weighted mean:</b> Useful for drug content calculations",
    ]:
        bullet(p, story)
    note("Always report which averaging method was used. Z-average (cumulant) is the "
         "standard for regulatory submissions.", story)

    teal_bar("2.2  Zeta Potential", story)
    body("<b>Principle:</b> Zeta potential measures the electrostatic potential at the "
         "slipping plane of the electrical double layer surrounding each droplet. It is "
         "a key indicator of colloidal stability – higher absolute values indicate "
         "greater electrostatic repulsion between droplets.", story)
    rows_zp = [
        ["< ±10 mV",    "Rapid coagulation/flocculation"],
        ["±10–20 mV",   "Incipient instability"],
        ["±20–30 mV",   "Moderate stability"],
        ["> ±30 mV",    "Good electrostatic stability"],
        ["> ±60 mV",    "Excellent stability"],
    ]
    story.extend(make_table(["Zeta Potential", "Stability Interpretation"],
                            rows_zp, [5.0*cm, 10.6*cm],
                            "Table 2: Zeta potential stability interpretation"))
    note("For sterically stabilized NEs (e.g., PEGylated), zeta potential may be "
         "low (±10–20 mV) yet stability is maintained via steric repulsion.", story)

    teal_bar("2.3  Polydispersity Index (PDI)", story)
    body("PDI is a dimensionless parameter derived from DLS cumulant analysis that "
         "quantifies the width of the droplet size distribution. It ranges from 0 "
         "(perfectly monodisperse) to 1 (highly polydisperse).", story)
    rows_pdi = [
        ["< 0.1",    "Highly monodisperse – ideal for parenteral use"],
        ["0.1–0.2",  "Narrow, acceptable distribution – preferred for topical NEs"],
        ["0.2–0.5",  "Moderately polydisperse – may compromise stability"],
        ["> 0.5",    "Highly polydisperse – formulation requires optimization"],
    ]
    story.extend(make_table(["PDI Range", "Interpretation"],
                            rows_pdi, [3.0*cm, 12.6*cm],
                            "Table 3: PDI interpretation"))

    teal_bar("2.4  Viscosity & Rheology", story)
    body("Viscosity determines the flow behavior, spreadability, and sensory properties "
         "of NE formulations. It is particularly important for topical/transdermal "
         "products.", story)
    for v in [
        "<b>Brookfield rotational viscometer:</b> Standard for Newtonian fluids (simple NEs)",
        "<b>Cone-and-plate rheometer:</b> For viscoelastic gels and nanoemulgels",
        "<b>Oscillatory rheology (G', G''):</b> Distinguishes elastic vs. viscous behavior",
        "<b>Flow curves:</b> Shear stress vs. shear rate to classify Newtonian/non-Newtonian behavior",
    ]:
        bullet(v, story)
    body("<b>Acceptance criteria:</b> NE viscosity typically 10–200 mPa·s (liquid); "
         "nanoemulgels 1,000–50,000 mPa·s depending on application.", story)

    teal_bar("2.5  Refractive Index & Transmittance", story)
    body("Refractive index (RI) is measured with a refractometer (Abbe refractometer) "
         "and provides information on composition and emulsion type. RI of a o/w NE "
         "is typically close to water (1.33–1.36).", story)
    body("<b>% Transmittance:</b> Measured by UV-Vis spectrophotometer at 650 nm using "
         "distilled water as blank. Values &gt;80% confirm nanosized, near-transparent "
         "system. Lower values indicate larger droplet sizes.", story)
    story.append(PageBreak())

    # ── SECTION 3: CHEMICAL CHARACTERIZATION ───────────────────────────────
    section_box("3", "Chemical Characterization Techniques", story)

    teal_bar("3.1  Drug Content & Encapsulation Efficiency (EE%)", story)
    body("Drug content quantifies the total drug in the formulation. EE% measures "
         "the fraction of drug successfully encapsulated within the oil droplets "
         "(vs. free drug in aqueous phase).", story)
    body("<b>Method:</b> Dissolve known NE volume in methanol or suitable solvent to "
         "rupture droplets. Analyze by HPLC or UV-Vis spectrophotometry against "
         "calibration curve.", story)
    body("<b>Formulae:</b>", story)
    formula_data = [[
        Paragraph("<b>Drug Content (%) =</b>  (Amount of drug found / Theoretical amount) × 100",
                  S("f", fontSize=10, fontName="Helvetica", textColor=NAVY,
                    leading=14, alignment=TA_CENTER)),
    ],[
        Paragraph("<b>EE (%) =</b>  [(Total drug – Free drug) / Total drug] × 100",
                  S("f2", fontSize=10, fontName="Helvetica", textColor=NAVY,
                    leading=14, alignment=TA_CENTER)),
    ]]
    ft = Table(formula_data, colWidths=[15.6*cm])
    ft.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),(-1,-1), HexColor("#EBF5FB")),
        ("TOPPADDING",    (0,0),(-1,-1), 8),
        ("BOTTOMPADDING", (0,0),(-1,-1), 8),
        ("BOX",           (0,0),(-1,-1), 1.0, TEAL),
        ("LINEABOVE",     (0,1),(-1,1), 0.5, MIDGREY),
    ]))
    story.append(ft)
    story.append(Spacer(1, 0.2*cm))
    note("Acceptance criterion: Drug content 95–105% of label claim; EE% >85% is "
         "considered good encapsulation.", story)

    teal_bar("3.2  FTIR Spectroscopy (Fourier Transform Infrared)", story)
    body("FTIR identifies functional groups and detects possible drug-excipient "
         "interactions or chemical incompatibilities. Key peaks are compared between "
         "pure drug, blank NE, and drug-loaded NE.", story)
    for f in [
        "Retention of characteristic drug peaks confirms drug integrity",
        "Shift or disappearance of peaks indicates molecular interaction",
        "New peaks suggest degradation or reaction products",
        "KBr pellet method or ATR-FTIR (attenuated total reflectance) are both acceptable",
    ]:
        bullet(f, story)

    teal_bar("3.3  Differential Scanning Calorimetry (DSC)", story)
    body("DSC measures heat flow as a function of temperature to detect melting points, "
         "glass transitions, crystallinity changes, and drug-excipient interactions. "
         "It confirms whether the drug is dissolved (amorphous) within the oil phase "
         "or retains its crystalline structure.", story)
    for d in [
        "<b>Loss of endothermic melting peak</b> – drug is solubilized/amorphous in the system",
        "<b>Shift in Tm</b> – interaction between drug and excipient",
        "<b>No change in peak</b> – no significant interaction, drug exists as crystals",
    ]:
        bullet(d, story)

    teal_bar("3.4  pH Measurement", story)
    body("pH must be measured for all topical/mucosal/ophthalmic NE formulations to "
         "ensure compatibility with the application site and to avoid irritation.", story)
    rows_ph = [
        ["Skin (topical)",          "4.5–6.5"],
        ["Vaginal mucosa",          "3.8–4.5"],
        ["Ocular (ophthalmic)",     "6.0–8.0"],
        ["Oral mucosa (buccal)",    "5.5–7.0"],
        ["Wound/burn surface",      "5.5–7.4"],
    ]
    story.extend(make_table(["Application Site", "Acceptable pH Range"],
                            rows_ph, [6.0*cm, 9.6*cm],
                            "Table 4: Target pH by application route"))

    teal_bar("3.5  Electrical Conductivity", story)
    body("Conductivity measurements distinguish between o/w (high conductivity, "
         "aqueous continuous phase) and w/o emulsions (low conductivity). Measured "
         "by conductivity meter at 25°C.", story)
    note("o/w nanoemulsion: conductivity typically 50–200 µS/cm. w/o nanoemulsion: "
         "<10 µS/cm.", story)
    story.append(PageBreak())

    # ── SECTION 4: MORPHOLOGICAL CHARACTERIZATION ───────────────────────────
    section_box("4", "Morphological Characterization", story)

    teal_bar("4.1  Transmission Electron Microscopy (TEM)", story)
    body("TEM provides direct visualization of nanoemulsion droplet morphology, size, "
         "and internal structure at the nanoscale. Negative staining (with 1–2% "
         "phosphotungstic acid or uranyl acetate) is commonly used.", story)
    for t in [
        "Confirms spherical, near-spherical, or irregular droplet morphology",
        "Directly measures droplet size (cross-validation with DLS)",
        "Detects drug crystallization within droplets",
        "Resolution: 0.1–1 nm; Magnification: up to 1,000,000×",
    ]:
        bullet(t, story)
    note("TEM measures the dry, dehydrated state. Size may appear slightly smaller "
         "than DLS (hydrodynamic) measurements due to loss of hydration shell.", story)

    teal_bar("4.2  Scanning Electron Microscopy (SEM)", story)
    body("SEM is used primarily for solid NE systems (dried, lyophilized, or "
         "incorporated into films/dressings). It provides surface topography at "
         "nanometer to micrometer resolution.", story)
    for s in [
        "Characterizes surface morphology of nanoemulsion-loaded solid matrices",
        "Evaluates porosity of polymeric bandages/films loaded with NEs",
        "Field emission SEM (FESEM) achieves higher resolution for sub-50 nm particles",
    ]:
        bullet(s, story)

    teal_bar("4.3  Atomic Force Microscopy (AFM)", story)
    body("AFM provides 3D topographical mapping of NE droplets at the nanoscale "
         "without the need for staining or vacuum conditions. It can measure droplet "
         "size, surface roughness, and mechanical properties (nanoindentation).", story)
    note("AFM is particularly valuable for measuring droplets adsorbed on surfaces "
         "and for real-time imaging in liquid environments.", story)
    story.append(PageBreak())

    # ── SECTION 5: STABILITY ─────────────────────────────────────────────────
    section_box("5", "Stability Characterization", story)
    body("Stability evaluation ensures the NE maintains its physical, chemical, and "
         "microbiological quality throughout its intended shelf life. Three tiers "
         "of stability testing are typically performed.", story)

    teal_bar("5.1  Thermodynamic Stability Tests (Short-term Screening)", story)
    body("These rapid stress tests screen out unstable formulations before proceeding "
         "to long-term studies. A formulation passing all three tests is considered "
         "thermodynamically stable.", story)
    rows_thermo = [
        ["Heating-Cooling Cycles",
         "6 cycles between 4°C and 45°C (48 h each)",
         "No phase separation, creaming, or drug precipitation"],
        ["Centrifugation Stress",
         "3,500–5,000 rpm for 30 min",
         "No phase separation; droplet size unchanged ±10%"],
        ["Freeze-Thaw Cycles",
         "3 cycles: -21°C (48 h) → +25°C (48 h)",
         "No coalescence; visual clarity retained"],
    ]
    story.extend(make_table(
        ["Test", "Conditions", "Acceptance Criterion"],
        rows_thermo,
        [4.0*cm, 5.8*cm, 5.8*cm],
        "Table 5: Thermodynamic stability test protocol"))

    teal_bar("5.2  Physical Stability – Long-term Storage", story)
    body("Stored at target conditions (e.g., 25°C/60% RH for room temperature; "
         "4°C for refrigerated). Samples analyzed at 0, 1, 3, 6, 9, 12 months.", story)
    for p in [
        "Droplet size (Z-average) – should not increase >20% from initial",
        "PDI – should remain <0.3",
        "Zeta potential – should not decrease in absolute value >10 mV",
        "pH – should remain within ±0.5 of initial",
        "Visual appearance – clarity, color, phase separation",
        "Drug content – should remain 90–110% of initial",
    ]:
        bullet(p, story)

    teal_bar("5.3  Accelerated Stability – ICH Q1A(R2) Guidelines", story)
    body("ICH-compliant accelerated studies predict shelf life and identify degradation "
         "pathways under stressed conditions.", story)
    rows_ich = [
        ["Long-term",       "25°C ± 2°C / 60% RH ± 5%",  "12–24 months",  "Shelf life determination"],
        ["Intermediate",    "30°C ± 2°C / 65% RH ± 5%",  "6–12 months",   "Significant change zone"],
        ["Accelerated",     "40°C ± 2°C / 75% RH ± 5%",  "6 months",      "Prediction of shelf life"],
        ["Photostability",  "ICH Q1B (UV + visible light)","Minimum 200 Wh/m²","Light sensitivity"],
    ]
    story.extend(make_table(
        ["Study Type", "Conditions", "Duration", "Purpose"],
        rows_ich,
        [3.2*cm, 5.0*cm, 3.2*cm, 4.2*cm],
        "Table 6: ICH stability testing conditions"))
    story.append(PageBreak())

    # ── SECTION 6: IN VITRO PERFORMANCE ─────────────────────────────────────
    section_box("6", "In Vitro Performance Testing", story)

    teal_bar("6.1  Drug Release Studies – Franz Diffusion Cell", story)
    body("The Franz diffusion cell is the gold standard for evaluating drug release "
         "from topical and transdermal formulations. It consists of a donor "
         "compartment (containing the NE formulation) separated from the receiver "
         "compartment by a synthetic or biological membrane.", story)
    for step in [
        "<b>Membrane:</b> Cellulose acetate (synthetic) or dialysis membrane; or excised human/porcine skin for ex vivo",
        "<b>Receptor fluid:</b> PBS pH 7.4 (skin/wound); pH 4.5 (vaginal); mixed solvents to maintain sink conditions",
        "<b>Temperature:</b> 32°C ± 0.5°C (skin surface temperature)",
        "<b>Stirring:</b> 600 rpm with magnetic stir bar in receptor compartment",
        "<b>Sampling:</b> Aliquots withdrawn at 1, 2, 4, 6, 8, 12, 24 h; replace with fresh receptor fluid",
        "<b>Analysis:</b> HPLC or UV-Vis; plot cumulative drug permeated (µg/cm²) vs. time",
    ]:
        bullet(step, story)
    body("<b>Release kinetic models applied:</b>", story)
    rows_kinetics = [
        ["Zero order",   "Q = Q₀ + K₀t",                 "Constant release rate; independent of concentration"],
        ["First order",  "log Q = log Q₀ – K₁t/2.303",   "Release proportional to remaining drug concentration"],
        ["Higuchi",      "Q = KH√t",                      "Diffusion-controlled release from matrix"],
        ["Korsmeyer-Peppas","Mt/M∞ = Ktn",               "n<0.45: Fickian; 0.45<n<0.89: anomalous transport"],
        ["Hixson-Crowell","Q₀^(1/3) – Qt^(1/3) = Kst",   "Surface erosion/dissolution model"],
    ]
    story.extend(make_table(
        ["Model", "Equation", "Interpretation"],
        rows_kinetics,
        [3.0*cm, 5.5*cm, 7.1*cm],
        "Table 7: Drug release kinetic models"))

    teal_bar("6.2  Ex Vivo Skin Permeation Study", story)
    body("Ex vivo permeation uses excised human cadaver skin or fresh porcine skin "
         "(structurally analogous to human skin) mounted on the Franz cell. Provides "
         "more physiologically relevant data than synthetic membranes.", story)
    for p in [
        "<b>Skin preparation:</b> Dermatomed to 400–500 µm; stratum corneum integrity verified by TEWL or impedance",
        "<b>Parameters:</b> Flux (µg/cm²/h), permeability coefficient (Kp), lag time (tlag), and cumulative drug permeated",
        "<b>Tape stripping:</b> Quantifies drug distribution across skin layers (stratum corneum, epidermis, dermis)",
    ]:
        bullet(p, story)

    teal_bar("6.3  Antimicrobial / Antifungal Activity – MIC Determination", story)
    body("Minimum Inhibitory Concentration (MIC) is the lowest concentration of a "
         "formulation that inhibits visible microbial growth. Standard reference "
         "organisms for antifungal NEs include <i>Candida albicans</i> ATCC 10231, "
         "<i>Trichophyton mentagrophytes</i>, and <i>Aspergillus niger</i>.", story)
    for m in [
        "<b>Broth microdilution (CLSI M27/M38):</b> Serial 2-fold dilutions in 96-well plate; 35°C, 24–48 h",
        "<b>Agar diffusion (disc/well):</b> Zone of inhibition (ZOI) measured in mm; compared to standard drug",
        "<b>MFC (Minimum Fungicidal Concentration):</b> Subculture from MIC wells; lowest conc. showing 99.9% kill",
        "<b>Time-kill kinetics:</b> CFU/mL vs. time curves at fixed drug concentrations",
    ]:
        bullet(m, story)
    story.append(PageBreak())

    # ── SECTION 7: BIOCOMPATIBILITY ──────────────────────────────────────────
    section_box("7", "Biocompatibility & Safety Tests", story)

    teal_bar("7.1  Cytotoxicity – MTT Assay", story)
    body("The MTT assay (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) "
         "measures mitochondrial activity as a surrogate for cell viability. It is the "
         "standard in vitro cytotoxicity screen for nanoemulsion formulations.", story)
    for m in [
        "<b>Cell lines:</b> HaCaT keratinocytes (skin), NIH 3T3 fibroblasts (wound healing), Vero cells",
        "<b>Procedure:</b> Seed cells, treat with NE dilutions (0.1–1000 µg/mL) for 24–72 h, add MTT reagent",
        "<b>IC₅₀:</b> Concentration inhibiting 50% cell viability; higher IC₅₀ = lower cytotoxicity",
        "<b>Acceptance:</b> Cell viability >80% at intended therapeutic concentration = biocompatible",
    ]:
        bullet(m, story)

    teal_bar("7.2  Skin Irritation Tests", story)
    body("In vivo skin irritation (Draize test on rabbits – OECD 404) has largely been "
         "replaced by validated in vitro alternatives.", story)
    rows_safety = [
        ["HET-CAM", "Hen's egg test on chorioallantoic membrane; grades vascular damage",
         "Score 0–21; <0.9 = non-irritant"],
        ["EpiDerm™ MTT", "Reconstituted human epidermis; ISO 10993-23 compliant",
         "Viability >50% = non-irritant"],
        ["RBC Haemolysis", "Red blood cell lysis assay; simple, low-cost screen",
         "<10% haemolysis = non-irritant"],
        ["BCOP", "Bovine corneal opacity test for ophthalmic NEs",
         "Score <3 = non-irritant"],
    ]
    story.extend(make_table(
        ["Test", "Description", "Acceptance Criterion"],
        rows_safety,
        [2.5*cm, 8.0*cm, 5.1*cm],
        "Table 8: In vitro skin/mucosa irritation tests"))
    note("For wound/burn applications, ISO 10993-5 (cytotoxicity) and ISO 10993-10 "
         "(sensitization) biocompatibility standards apply.", story)
    story.append(PageBreak())

    # ── SECTION 8: ACCEPTANCE CRITERIA SUMMARY ──────────────────────────────
    section_box("8", "Acceptance Criteria Summary Table", story)
    body("The following table consolidates acceptance criteria for all key "
         "characterization parameters of topical/transdermal nanoemulsion formulations.", story)
    story.append(Spacer(1, 0.2*cm))
    rows_ac = [
        ["Droplet size (Z-avg)", "DLS (Zetasizer)",    "<200 nm (topical); <100 nm (optimal)"],
        ["PDI",                   "DLS",                "<0.2 (preferred); <0.3 (acceptable)"],
        ["Zeta potential",        "Electrophoresis",    ">±20 mV; >±30 mV (good stability)"],
        ["pH",                    "pH meter",           "Application site-specific (see Table 4)"],
        ["Viscosity (liquid NE)", "Viscometer",         "10–200 mPa·s"],
        ["% Transmittance",       "UV-Vis @ 650 nm",    ">80%"],
        ["Refractive index",      "Refractometer",      "1.33–1.40 (o/w NE)"],
        ["Drug content",          "HPLC/UV-Vis",        "95–105%"],
        ["Encapsulation Eff.",    "Centrifugation + HPLC", ">85%"],
        ["Conductivity (o/w NE)", "Conductivity meter", "50–200 µS/cm"],
        ["Long-term stability",   "Storage (0–12 mo.)", "Size ±20%; PDI <0.3; ZP ±10 mV"],
        ["Thermodynamic stability","H-C, F-T, centrifuge","Pass all 3 stress tests"],
        ["Drug release (24 h)",   "Franz cell",         ">80% for immediate; per specification"],
        ["Cell viability (MTT)",  "In vitro (HaCaT)",   ">80% at therapeutic dose"],
        ["Skin irritation",       "HET-CAM/EpiDerm",    "Non-irritant classification"],
        ["Antimicrobial activity","MIC (broth dilution)","MIC ≤ reference standard drug"],
    ]
    story.extend(make_table(
        ["Parameter", "Method", "Acceptance Criterion"],
        rows_ac,
        [4.0*cm, 4.6*cm, 7.0*cm],
        "Table 9: Comprehensive acceptance criteria for NE characterization"))
    story.append(PageBreak())

    # ── SECTION 9: TROUBLESHOOTING ───────────────────────────────────────────
    section_box("9", "Troubleshooting Guide", story)
    body("Common issues encountered during nanoemulsion formulation and characterization, "
         "with recommended solutions:", story)
    story.append(Spacer(1, 0.1*cm))
    rows_ts = [
        ["Large droplet size\n(>500 nm)",
         "Insufficient surfactant concentration; low energy input; poor oil selection",
         "Increase Smix ratio; add more homogenization passes; screen other oils"],
        ["High PDI (>0.3)",
         "Polydisperse droplet population; coalescence during prep",
         "Optimize surfactant:co-surfactant ratio; use microfluidizer; add co-emulsifier"],
        ["Low zeta potential\n(<±15 mV)",
         "Insufficient surface charge; neutral surfactants dominate",
         "Add ionic surfactant (SDS/lecithin); adjust pH; use charged stabilizer"],
        ["Phase separation\non storage",
         "Ostwald ripening; coalescence; temperature fluctuations",
         "Add Ostwald ripening inhibitor (e.g., hexadecane); improve surfactant film"],
        ["Low drug content\n(<90%)",
         "Drug adsorption to container; poor solubility in oil; degradation",
         "Use glass containers; optimize oil selection; add antioxidant/chelator"],
        ["Low encapsulation\nefficiency (<80%)",
         "Drug partitioning to aqueous phase; insufficient oil phase volume",
         "Increase oil phase ratio; select oil with higher drug solubility"],
        ["Creaming/sedimentation",
         "Density mismatch between oil and water; large droplets",
         "Match densities; reduce droplet size; increase viscosity of continuous phase"],
        ["Drug precipitation\non cooling",
         "Drug supersaturation in oil phase at low temperature",
         "Reduce drug loading; add co-solvent; use amorphous form of drug"],
    ]
    # Render troubleshooting as mini 3-col table
    ts_style = S("ts", fontSize=9, fontName="Helvetica", leading=12,
                 textColor=BLACK)
    ts_bold  = S("tsb", fontSize=9, fontName="Helvetica-Bold", leading=12,
                 textColor=NAVY)
    ts_data = [[header_cell("Problem"), header_cell("Possible Cause"),
                header_cell("Recommended Solution")]]
    for prob, cause, sol in rows_ts:
        ts_data.append([
            Paragraph(prob, ts_bold),
            Paragraph(cause, ts_style),
            Paragraph(sol, ts_style),
        ])
    ts_table = Table(ts_data, colWidths=[3.5*cm, 5.5*cm, 6.6*cm], repeatRows=1)
    ts_table.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),(-1,0), NAVY),
        ("ROWBACKGROUNDS",(0,1),(-1,-1), [LTGREY, WHITE]),
        ("GRID",          (0,0),(-1,-1), 0.4, MIDGREY),
        ("TOPPADDING",    (0,0),(-1,-1), 5),
        ("BOTTOMPADDING", (0,0),(-1,-1), 5),
        ("LEFTPADDING",   (0,0),(-1,-1), 6),
        ("VALIGN",        (0,0),(-1,-1), "TOP"),
    ]))
    story.append(Paragraph("Table 10: Nanoemulsion troubleshooting guide",
                           style_caption))
    story.append(ts_table)
    story.append(PageBreak())

    # ── SECTION 10: REFERENCES ──────────────────────────────────────────────
    section_box("10", "Key References", story)
    refs = [
        ("1", "Sosnowska K, Szymanska E, Winnicka K. Nanoemulsion with Clotrimazole – "
              "Design and Optimalization of Mean Droplet Size Using Microfluidization. "
              "<i>Acta Pol Pharm.</i> 2017. PMID: 29624257"),
        ("2", "Soriano-Ruiz JL et al. Biopharmaceutical profile of a clotrimazole nanoemulsion: "
              "Evaluation on skin and mucosae as anticandidal agent. "
              "<i>Int J Pharm.</i> 2019. DOI: 10.1016/j.ijpharm.2018.11.002"),
        ("3", "Smolenski M et al. Nanoemulsion Loaded with Clotrimazole Based on Rapeseed Oil "
              "for Potential Vaginal Application. <i>Pharmaceutics.</i> 2023. PMC10224398"),
        ("4", "Khorsand F et al. Nanoemulsion-Based Tea Tree Oil: A New Frontier in Enhancing "
              "Clotrimazole Antifungal Activity. <i>Mol Biotechnol.</i> 2026. PMID: 40716017"),
        ("5", "Patel P et al. Formulation and Development of Clotrimazole Nanoemulsion for "
              "Topical Delivery by QbD Approach. <i>Int J Pharm Res Appl.</i> 2023;8(3):1727-1752"),
        ("6", "McClements DJ. Nanoemulsions versus Microemulsions: Terminology, Differences, "
              "and Similarities. <i>Soft Matter.</i> 2012;8:1719-1729"),
        ("7", "Gurpreet K, Singh SK. Review of Nanoemulsion Formulation and Characterization "
              "Techniques. <i>Indian J Pharm Sci.</i> 2018;80(5):781-789"),
        ("8", "ICH Q1A(R2). Stability Testing of New Drug Substances and Products. "
              "International Council for Harmonisation, 2003"),
        ("9", "CLSI M27-A3. Reference Method for Broth Dilution Antifungal Susceptibility "
              "Testing of Yeasts. Clinical and Laboratory Standards Institute, 2017"),
        ("10", "ISO 10993-5:2009. Biological evaluation of medical devices – "
               "Tests for cytotoxicity (in vitro methods)"),
    ]
    ref_style = S("ref", fontSize=9.5, fontName="Helvetica", textColor=BLACK,
                  leading=14, spaceAfter=5, leftIndent=24, firstLineIndent=-18)
    for num, ref in refs:
        story.append(Paragraph(f"[{num}]  {ref}", ref_style))
    story.append(Spacer(1, 0.5*cm))
    story.append(HRFlowable(width="100%", thickness=1, color=TEAL, spaceAfter=10))

    # Footer disclaimer
    disc_data = [[
        Paragraph(
            "This guide is intended as an educational and research reference. "
            "Always consult current pharmacopoeial monographs (USP, EP, IP), "
            "ICH guidelines, and regulatory guidance documents for validated "
            "methods applicable to GMP/regulatory submissions.",
            S("disc", fontSize=8.5, fontName="Helvetica-Oblique",
              textColor=HexColor("#555555"), leading=12, alignment=TA_CENTER))
    ]]
    dt = Table(disc_data, colWidths=[15.6*cm])
    dt.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),(-1,-1), HexColor("#F0F3F4")),
        ("LEFTPADDING",   (0,0),(-1,-1), 12),
        ("TOPPADDING",    (0,0),(-1,-1), 8),
        ("BOTTOMPADDING", (0,0),(-1,-1), 8),
        ("BOX",           (0,0),(-1,-1), 0.5, MIDGREY),
    ]))
    story.append(dt)

    # ── BUILD ─────────────────────────────────────────────────────────────────
    doc.build(story)
    print(f"PDF generated: {OUTPUT}")

build_pdf()

Successfully replaced 1 instance(s) of the string in '/tmp/workspace/nanoemulsion-guide/generate_guide.py'

Successfully replaced 1 instance(s) of the string in '/tmp/workspace/nanoemulsion-guide/generate_guide.py'