Ep 21 — Pharmaceutical Industry: API Identification and Quality Control

Series: Infrared Spectroscopy Encyclopedia: From Principles to Practice
Chapter: Part 3 · Intermediate — Industry Applications
Target Audience: QC/QA personnel in pharmaceutical companies, technicians in drug testing institutes, pharmaceutical research and registration personnel
Prerequisites: Ep 13 (Transmission), Ep 14 (ATR), Ep 19 (Library Search), Ep 20 (Quantitative Basics)
Reading Time: Approximately 45 minutes

Introduction: An IR Spectrum That Stopped a "Fake Drug"

In 2012, a provincial drug testing institute received a batch of imported samples labeled as "Aspirin Enteric-Coated Tablets." The appearance and packaging were almost flawless, and the HPLC content was also "qualified." However, when the inspector performed infrared identification according to Chinese Pharmacopoeia (ChP) General Chapter 0402, the spectrum revealed the truth—the sample lacked the characteristic carbonyl peak of acetylsalicylic acid at 1680 cm⁻¹, and instead showed a strong unfamiliar absorption at 1640 cm⁻¹ [1].

Further comparison revealed that the actual raw material of this batch of "aspirin" was paracetamol—a completely different antipyretic and analgesic drug, low in cost, used by unscrupulous manufacturers to substitute for aspirin. The reason the HPLC content was "qualified" is that the method only measured the "main component content" without structural identification [1].

"Infrared spectrophotometry has been used for identification purposes in pharmacopoeias for over 50 years, and remains one of the most specific yet simplest identification tests."
—— Ph. Eur. General Chapter 2.2.24 [2]

This real case reveals an iron rule in the pharmaceutical industry: Qualified content does not equal genuine product; structural identification is the gold standard for identity verification. And infrared spectroscopic identification is the "ID verification" method jointly recognized by global pharmacopoeias.

This episode is the first in the "Intermediate · Industry Applications" section. We will delve into pharmaceutical QC laboratories, systematically study the application of FTIR in the identification and quality control of Active Pharmaceutical Ingredients (APIs), understand the methodological logic behind pharmacopoeias, and grasp practical points in GMP environments.

1. Why Do Pharmacopoeias Rely So Heavily on Infrared Identification?

1.1 General Chapters on IR Identification in Three Major Pharmacopoeias

Global pharmacopoeias have specific general chapters for infrared identification, with highly consistent methodological frameworks [2][3][4]:

Common Logic [2][3][4]:

1. Sample and reference standard (CRS) are prepared and measured using the same method and instrument.
2. Compare the two spectra; the positions of the strongest absorption bands and their relative intensities should match.
3. Minor differences in baseline tilt and intensity due to grinding variations are allowed.
4. If discrepancies exist, re-prepare the sample for confirmation.

💡 Key Insight: The essence of pharmacopoeial IR identification is an identity test, not structural elucidation. It answers "Is this the compound?" rather than "What compound is this?"

1.2 Why Choose IR Over Other Techniques?

USP \<197> lists four identification methods: UV, IR, TLC, and HPLC. However, IR is considered the most specific method [4] due to the following reasons:

• High peak density: An organic drug typically has 20–50 distinguishable absorption bands in the mid-IR region, equivalent to a "molecular fingerprint."
• Stable band positions: Vibrational frequencies are determined by bond force constants and atomic masses, with little influence from solvent or concentration.
• Full spectrum comparison: Peak-by-peak comparison with a reference spectrum yields an extremely low false positive rate.
• Simple method: KBr pellet method yields results within 10 minutes, much faster than NMR or MS.

In comparison:

• UV has only 2–3 broad peaks, poor specificity, and often cannot distinguish isomers.
• TLC only relies on Rf values and is easily affected by impurities.
• HPLC identification depends on retention time; column efficiency degradation or mobile phase deviations can lead to misjudgment.

"The IR spectrum of a compound is generally more characteristic than its UV or NMR spectrum for identification purposes, since it typically contains numerous sharp peaks across a wide frequency range."
—— USP General Chapter \<197> [4]

1.3 Authoritative Sources of Reference Spectra

Each pharmacopoeia provides an official collection of reference IR spectra [2][3][4]:

• Chinese Pharmacopoeia (ChP): Drug Infrared Spectrum Collection (previous editions, latest is Volume 5, 2015 edition)
• USP: USP IR Spectra Database (accompanying USP Reference Standards, CRS)
• Ph. Eur.: European Pharmacopoeia IR Reference Spectra (available online at the Pharmeuropa website)

⚠️ Note: Caution should be exercised when using commercial spectral libraries (e.g., Sadtler, Sigma-Aldrich) for pharmacopoeial identification, as their sample preparation methods may differ (e.g., KBr pellet vs. ATR), leading to differences in band positions and intensities. Pharmacopoeial identification should use official pharmacopoeia spectra or actual measurement of reference standards [3][4].

2. Standard Procedure for API Identification

2.1 KBr Pellet Method: The "Classic Orthodox" of Pharmacopoeias

Although ATR is common in routine research, the official method for pharmacopoeial IR identification is still primarily KBr pelleting [2][3][4]. Reasons include:

• KBr pellet spectra are fully comparable with historical reference spectra (same preparation method).
• Pathlength is precisely controllable (approximately 0.5–1 mg sample dispersed in 200 mg KBr).
• Spectral morphology is standard, with no anomalous dispersion shifts in band positions as in ATR.

ChP 0402 General Chapter Standard Procedure [3]:

   API Sample (1–2 mg)
        │
        ▼
   Agate mortar + 200 mg dry KBr
        │ Grind thoroughly for 1–2 min
        │ Particle size < 2 μm
        ▼
   Load into 13 mm die
        │ Evacuate for 1 min
        │ Apply 7–10 tons pressure for 1–2 min
        ▼
   Transparent KBr pellet
        │ Place in sample holder
        ▼
   FTIR acquisition (4 cm⁻¹ resolution, 16–32 scans)
        │
        ▼
   Compare with reference spectrum (prepared similarly) or pharmacopoeial standard spectrum

📷 Figure 1: Standard operating procedure for KBr pellet method
Source: Training materials from the National Institutes for Food and Drug Control (NIFDC) [3]
https://www.nifdc.org.cn/

2.2 Criteria for Spectral Comparison

The pharmacopoeial general chapters provide the following criteria [2][3][4]:

① Band position agreement: The wavenumber of main absorption bands in the sample and reference should match. Laboratories often use an empirical tolerance of about ±2 cm⁻¹ for strong bands (depending on the pharmacopoeia/validation document); if multiple strong bands shift consistently in the same direction, investigate crystal form, reference standard, and calibration; do not set contradictory relaxed thresholds.

② Intensity distribution agreement: The relative intensities (strong/medium/weak) should match; absolute absorbance values need not be identical (due to slight variations in concentration and pathlength).

③ Fingerprint region must be compared: Many beginners only look at the functional group region (4000–1500 cm⁻¹), but pharmacopoeias require the fingerprint region (1500–400 cm⁻¹) to also match—this is key for distinguishing isomers and homologues.

④ Permitted differences [2][3]:

• Baseline tilt (due to KBr particle scattering)

• Slight differences in overall intensity (due to uneven sample dispersion)

• Missing weak peaks (differences in signal-to-noise ratio)

⑤ Impermissible differences [2][3]:

• Systematic large shifts in strong peak positions (significantly above the empirical threshold of about ±2 cm⁻¹, with multiple peaks shifting in the same direction)——first check crystal form/reference substance/calibration, rather than using another set of informal thresholds that contradict each other
• Appearance of new medium or strong intensity peaks
• Disappearance of strong peaks

2.3 A Typical Example: Infrared Identification of Aspirin

Aspirin (acetylsalicylic acid, C₉H₈O₄) is a classic non-steroidal anti-inflammatory drug. Its infrared characteristic peak assignments are as follows [5]:

🔗 Extension: Aspirin contains both carboxyl and ester functional groups. The frequency distribution of carboxylic acid C=O in the 1650–1730 cm⁻¹ range can be found at ftir.fun carboxyl functional group page – carboxylic acid C=O is typically 20–40 cm⁻¹ lower than the free state due to hydrogen-bonded dimerization. For the ester C=O position, see ftir.fun ester functional group page, usually at 1735–1750 cm⁻¹ [6][7].

📷 Figure 2: Infrared spectrum of aspirin KBr pellet (with peak annotations)
Source: NIST Chemistry WebBook
https://webbook.nist.gov/cgi/…

If the two strong peaks at 1750 cm⁻¹ and 1680 cm⁻¹ show significant shift (e.g., shifting to a single peak at 1640 cm⁻¹) in the sample spectrum, it can be basically determined that it is not aspirin – this is precisely the spectral feature of the "fake aspirin" case mentioned in the introduction [1].

III. Identification and Exclusion of Excipient Interference

3.1 Differences between Formulation and API Identification

Infrared identification of active pharmaceutical ingredients (API) is relatively straightforward – the main component is the target substance. However, formulations (tablets, capsules, granules) present much more complexity in IR identification because [8]:

• API content in formulations may be only 5–30% (or even lower)
• Excipients (e.g., lactose, starch, microcrystalline cellulose, magnesium stearate) account for a large proportion
• Excipients themselves have strong IR absorption, which can seriously interfere with API peaks

3.2 Infrared "Fingerprints" of Common Excipients

The following table lists the most commonly used excipients in pharmaceuticals and their characteristic absorptions [8][9]:

Key Observations [8][9]:

• Sugar excipients (lactose, MCC, starch) have very strong O-H at 3300 cm⁻¹ and C-O at 1000–1150 cm⁻¹, which can completely cover API peaks in these regions
• Magnesium stearate has very strong aliphatic chain peaks at 2920/2850 cm⁻¹, which can interfere with API C-H peaks
• Croscarmellose sodium has COO⁻ near 1600 cm⁻¹, potentially overlapping with API C=O, Amide I

3.3 Three Strategies to Exclude Excipient Interference

Strategy 1: Extraction method (preferred) [8][9]

Crush the formulation and extract the API with a suitable solvent, filter to remove excipients, evaporate the solvent, and measure the residue.

• Aspirin tablets: Extract API with ethanol, filter to remove lactose/MCC
• Sulfonamide tablets: Extract with dilute acid or base, adjust pH to precipitate API
• Steroid hormone tablets: Extract with chloroform

Advantages: Obtain relatively pure API spectrum for direct comparison with pharmacopoeia reference spectra
Caution: Solvents may alter the crystal form of the API (see Ep 22); choose solvents that do not affect crystal form

Strategy 2: Spectral subtraction method

Collect the formulation spectrum $A{mix}$ and the excipient spectrum $A{exc}$ (prepared according to the formulation ratio), then compute the difference spectrum:

$$A_{API} \approx A_{mix} - \alpha \cdot A_{exc}$$

where $\alpha$ is the excipient proportion in the formulation.

Applicability: API content ≥ 20%, excipient spectrum known
Limitations: Spectral subtraction requires high accuracy in sample amount and only subtracts "known" excipients

Strategy 3: ATR method + selective peaks

Directly measure the formulation by ATR, and compare characteristic peaks with minimal excipient interference.

Case [9]: Compound formulation containing sulfamethoxazole (SMZ)

• SMZ N-H stretch at 3350/3280 cm⁻¹ (primary amine doublet)
• Lactose O-H at 3300 cm⁻¹ is also a broad peak
• However, SMZ peaks at 1595 cm⁻¹ (benzene ring) and 1150 cm⁻¹ (S=O) have almost no excipient interference
• Comparing these two peaks is sufficient to confirm the presence of SMZ

💡 Practical Experience: The most severe excipient interference is not in the functional group region, but rather in the 1000–1150 cm⁻¹ C-O region. Selecting aromatic ring C=C (1500–1600 cm⁻¹) and heteroatom peaks (S=O, P=O, C-F) of the API as diagnostic peaks is more reliable than forcing a full-spectrum comparison.

IV. Polymorphism Tips (See Ep 22)

API identification can sometimes be affected by crystal form differences: different polymorphs of the same API may cause shifts of several wavenumbers in peaks such as C=O and N–H due to differences in hydrogen bonding/conformation, leading to "incomplete consistency" with the reference substance. Pharmacopoeias often require specifying the crystal form for drugs prone to polymorphism [3][4].

This edition only keeps this reminder: If overall peak shifts are accompanied by changes in hydrogen-bond-related peaks, initiate crystal form investigation. Complete cases, peak tables, and event histories for carbamazepine, phenytoin, ritonavir, etc., are detailed in Ep 22; no repetition here.

🔗 For crystal-sensitive peaks of amide drugs, first consult ftir.fun amide page, then proceed to Ep 22 for systematic learning.

V. Pharmaceutical Quality Control: Content Uniformity and Dissolution

5.1 Role of IR in Content Uniformity (CU)

Content Uniformity (CU) is a critical QC item for tablets/capsules, requiring that the variation of active ingredient content among individual units be within allowable limits [3][4]. Traditional method is HPLC, but near-infrared (NIR) and ATR-FTIR online rapid screening have gradually entered pharmacopoeias [3].

Strategies for FTIR in CU:

① Single-tablet ATR-FTIR measurement

• Each tablet is directly pressed against the ATR crystal
• Measure the peak area of a characteristic API band (e.g., C=O)
• Convert to content via a calibration curve

Applicability: API content ≥ 25%, characteristic peak not interfered by excipients

Advantages: Single measurement takes 1–2 minutes, much faster than HPLC

② Combined with chemometrics for quantification (see Ep 43)

• Full spectrum or selected wavenumber ranges for PLS modeling
• Model predicts API content
• Suitable for low API content (< 10%) or formulations with severe excipient interference

5.2 Dissolution Monitoring

Dissolution is a critical quality attribute for solid dosage forms. USP General Chapter <711> and ChP General Chapter 0931 specify dissolution testing methods [3][4]. FTIR applications in dissolution mainly include [13]:

① Online monitoring of dissolution medium

• Dissolution medium circulates through an ATR flow cell
• Real-time determination of API concentration
• Advantages: no sampling, filtration, or dilution required

② Dissolution imaging (FPA-ATR)

• Use FPA focal plane array to observe chemical imaging of tablet dissolution in medium
• Visualize the tablet surface erosion process
• Distinguish different dissolution rates of API and excipients

📷 Figure 4: FPA-ATR imaging of drug tablet erosion process
Source: Kazarian group, Imperial College London [13]
https://doi.org/10.1517/17425…

💡 Professional Tip: When directly measuring dissolution medium with ATR, note that API concentration in dissolution medium is usually very low (μg/mL level), and the penetration depth of conventional ATR is only 1–2 μm, often insufficient sensitivity. Common solutions include [13]:

• Long-path transmission cell (ZnSe/CaF₂ windows, 0.1–1 mm path length)
• Pre-concentration (solid-phase extraction followed by measurement)

VI. Infrared Instrument Management and Documentation under GMP

6.1 Core GMP Requirements for Analytical Instruments

Good Manufacturing Practice (GMP) requires that all analytical instruments affecting product quality must undergo validation, and infrared instruments are no exception [14][15]. Main requirements are as follows:

① IQ (Installation Qualification)

• Instrument model and serial number verification
• Installation environment confirmation (temperature, humidity, vibration, power supply)
• Accessories list confirmation (ATR, KBr pellet press, etc.)
• Software version and user access control confirmation

② OQ (Operational Qualification)

• Wavenumber accuracy: Calibration using polystyrene film standard (e.g., 1601.4 cm⁻¹, 2850.5 cm⁻¹, 3082 cm⁻¹)
• Wavenumber precision: 6 consecutive polystyrene spectra, standard deviation < 0.1 cm⁻¹
• Transmittance accuracy: Deviation of %T of specified polystyrene peaks from nominal values
• Resolution: Peak-valley depth of polystyrene at 2870–1583 cm⁻¹ should meet pharmacopoeia requirements (e.g., ≥ 12%)
• Signal-to-noise ratio: Collect background under specified conditions, calculate peak-to-peak noise

③ PQ (Performance Qualification)

• Use representative API reference standard to verify method feasibility
• Periodic (e.g., monthly or quarterly) performance review
• Re-qualify IQ/OQ/PQ after instrument changes (e.g., source or beamsplitter replacement)

6.2 Instrument Usage Logs and Electronic Records

GMP requires all instrument usage to be traceable [14][15]:

• Usage log: Date, operator, sample ID, method, instrument status for each use
• Maintenance log: Source replacement, desiccant replacement, ATR crystal cleaning, etc.
• Calibration records: Periodic polystyrene calibration results
• Electronic data: Raw interferograms and spectral files must be retained, cannot be deleted or overwritten

21 CFR Part 11 (Electronic Records/Electronic Signatures) requirements [15]:

• Software must have audit trail functionality
• User access levels (operator, reviewer, administrator)
• Both raw data and processed data must be retained
• System time cannot be arbitrarily changed

6.3 Method Validation (USP <1225>)

Any infrared method used for QC must be validated per USP <1225> or ICH Q2(R2) [4][16]:

Table 1: Infrared method validation requirements (Data sources: USP <1225> [4], ICH Q2(R2) [16])

The core of identity is specificity – it must be demonstrated that [4]:

• Different batches of the same API → consistent spectra
• Different drugs with similar structures (e.g., aspirin vs. acetaminophen) → distinguishable spectra
• Major excipients do not interfere with the API's key peaks

VII. Real-World FTIR Pitfalls in Pharmaceutical QC

7.1 Pitfall 1: KBr Moisture Absorption Leading to Misjudgment

Case [3]: A QC lab tested the infrared identity of an extract residue from a formulation. The spectrum showed strong peaks at 3400 cm⁻¹ and 1640 cm⁻¹, which were misjudged as "sample containing water." After re-drying KBr and retesting, the two peaks disappeared, confirming KBr moisture absorption.

Lessons:

• KBr must be dried at 130 °C for ≥ 24 h and stored in a desiccator
• During high humidity seasons (humidity > 60%), pellet pressing should be performed in a glove box
• Peaks at 3400 cm⁻¹ and 1640 cm⁻¹ are "water fingerprints"; if observed, first check KBr

7.2 Pitfall 2: ATR Replacing KBr Without Method Validation

Case [17]: To speed up routine identification, a factory changed the pharmacopoeia-specified KBr pellet method to ATR without method validation. During an audit, a FDA Form 483 warning letter was issued because "ATR spectra have systematic differences from pharmacopoeia reference spectra."

Reason: ATR spectra exhibit low-wavenumber enhancement, and strong peak positions may shift by 2–5 cm⁻¹, leading to "misidentification" when directly compared to pharmacopoeia KBr spectra.

Correct practice [17]:

• If ATR is to replace KBr, method equivalence must be validated per USP <1854> or Ph. Eur. 2.2.24
• It is recommended to build an in-house ATR spectral library (measured using reference standards), rather than directly comparing with pharmacopoeia KBr spectra
• Method changes must follow change control procedures, be revalidated, and be reported to regulators

7.3 Pitfall 3: Unrecognized Polymorph Change

Case [11]: A raw material manufacturer produced sulfadiazine. One batch's infrared identity was "basically consistent" but showed a new peak at 1320 cm⁻¹. QC staff dismissed it as "instrument noise." Later, customers complained about "dissolution failure." Re-testing revealed that the batch had converted to another polymorph.

Lessons:

• Spectral comparison should not focus only on major peaks; weak peak changes in the fingerprint region should alert to polymorph changes
• Unexplained new peaks should be investigated by XRD, DSC to confirm polymorph
• For polymorphic drugs, QC should establish a "polymorph monitoring spectrum" – record allowable peak position ranges

7.4 Pitfall 4: Extraction of Excipients Alters Polymorph

Case [9]: A tablet identity test used methanol to extract the API. The infrared spectrum slightly differed from the pharmacopoeia standard. The cause was methanol-induced conversion of the API to a solvate.

Lessons:

• Extraction solvent must not affect API polymorph
• Prefer non-polar solvents (e.g., chloroform, dichloromethane)
• After extraction, the temperature for solvent evaporation should not exceed the API's polymorph conversion temperature

7.5 Pitfall 5: Untimely Instrument Performance Calibration

Case [14]: A QC lab failed to perform polystyrene calibration for three consecutive months. During this period, source energy decay caused a wavenumber shift of 1.5 cm⁻¹. All API spectra measured during this period had lower peak positions, which were traced back during an audit.

Lessons:

• Polystyrene calibration should be performed at least monthly
• Re-calibration is mandatory after replacing the source, beamsplitter, or detector
• Re-qualify IQ/OQ/PQ after instrument relocation

Summary of This Episode

| Criteria | Strong peak positions ±2 cm⁻¹, consistent relative intensities, fingerprint region must be matched |
| KBr pellet key points | Dry KBr (130 °C/24 h), grind < 2 μm, press at 7–10 tons |
| Excipient interference removal | Extraction method (preferred), difference spectroscopy, ATR selective peaks |
| Polymorph differentiation | Shift of hydrogen-bond-related peaks by 5–30 cm⁻¹, must be confirmed with XRD/DSC |
| GMP instrument management | IQ/OQ/PQ three-level validation, regular polystyrene calibration, traceable electronic records |
| Method validation | Identification focuses on specificity; quantitation requires full validation (USP <1225>) |
| Common pitfalls | KBr moisture absorption, unvalidated ATR substitution, missed polymorph changes, extraction-induced crystallization, missing calibration |

Thought Questions

1. In the KBr pellet spectrum of aspirin, the two C=O peaks at 1680 cm⁻¹ and 1750 cm⁻¹ belong to which functional groups? Why is one of the wavenumbers significantly lower than typical ester/carboxylic acid C=O? Please explain with reference to the ftir.fun carboxyl page and ester page.

2. A certain tablet contains 5% API (structure includes an amide group) and 90% lactose. When measured directly by ATR, the amide I peak is severely interfered by lactose absorption. Design two schemes to complete IR identification and state their respective advantages and disadvantages.

3. You are a QC manager in a pharmaceutical factory. A new FTIR with diamond ATR has been purchased, and you wish to replace traditional KBr pellet with ATR for routine identification. Please list the method validation checklist you need to perform (refer to USP <1854>).

4. The infrared spectrum of a batch of carbamazepine API shows a shift of C=O from 1672 cm⁻¹ to 1680 cm⁻¹, and the positions of the N-H double peaks also change slightly. What judgment would you make? What further tests are needed to confirm?

5. GMP inspectors find that your laboratory's infrared spectrometer has not undergone polystyrene calibration for two consecutive months, but routine QC identification has been ongoing. Please explain the potential risks of this violation and develop corrective and preventive actions (CAPA).

References

[1] National Medical Products Administration. Drug Inspection Information Bulletin (Compilation of Typical Cases). China Food and Drug Inspection Institute, 2013.
https://www.nifdc.org.cn/

[2] European Directorate for the Quality of Medicines & HealthCare (EDQM). European Pharmacopoeia 11th ed., General Chapter 2.2.24 "Absorption Spectrophotometry, Infrared". Council of Europe, 2023.
https://www.edqm.eu/en/europe…

[3] Chinese Pharmacopoeia Commission. Pharmacopoeia of the People's Republic of China 2020 Edition, Part IV General Chapter 0402 Infrared Spectrophotometry. China Medical Science Press.

[4] United States Pharmacopeial Convention. United States Pharmacopeia 2024, General Chapter \<197> "Spectrophotometric Identification Tests" and \<1854> "Mid-Infrared Spectroscopy". USP.

[5] Socrates G. Infrared and Raman Characteristic Group Frequencies. 3rd ed. Wiley, 2004. Chapter 8 (Carboxylic Acids and Esters). ISBN: 978-0-470-09307-8.

[6] ftir.fun. "Carboxyl (COOH) — FTIR absorption peaks and assignments." FTIR Functional Group Database.
https://ftir.fun/ir/group/car…

[7] ftir.fun. "Ester — FTIR absorption peaks and assignments." FTIR Functional Group Database.
https://ftir.fun/ir/group/est…

[8] Bugay D E. "Characterization of the Solid-State: Spectroscopic Techniques." Advances in Drug Delivery Reviews, 2001, 48(1): 43–65. DOI:10.1016/S0169-409X(01)00102-5.

[9] Bugay D E, Findlay W P. Pharmaceutical Excipients Characterization by IR, Raman, and NMR Spectroscopy. Marcel Dekker, 1999.

[10] Grzeszczak S et al. "Polymorphism in Carbamazepine: FTIR and DSC Studies." European Journal of Pharmaceutical Sciences, 2019, 128: 95–103. DOI:10.1016/j.ejps.2018.09.012.

[11] Brittain H G (ed.). Polymorphism in Pharmaceutical Solids. 2nd ed. CRC Press, 2016. Chapter 1 (Phenytoin Case) and Chapter 4 (Carbamazepine).

[12] ftir.fun. "Amide — FTIR absorption peaks and assignments." FTIR Functional Group Database.
https://ftir.fun/ir/group/ami…

[13] Kazarian S G, Ewing A V. "Applications of FTIR Spectroscopic Imaging to Tablet Dissolution and Drug Release." Expert Opinion on Drug Delivery, 2013, 10(9): 1207–1221. DOI:10.1517/17425247.2013.802832.

[14] PIC/S. Good Manufacturing Practice for Medicinal Products. PE 009-17, 2023. Chapter 3 (Premises and Equipment) and Chapter 6 (Quality Control).
https://picscheme.org/

[15] U.S. Food and Drug Administration. 21 CFR Part 11 — Electronic Records; Electronic Signatures. FDA, 2023.

[16] International Council for Harmonisation. ICH Q2(R2) Validation of Analytical Procedures. ICH, 2023.
https://www.ich.org/page/qual…

[17] USP General Chapter \<1854>. "Mid-Infrared Spectroscopy." United States Pharmacopeia.

Next Episode Preview: Ep 22 — Pharmaceutical Industry: Drug Crystal Form Analysis and Polymorph Detection

We will focus on polymorphism, a "minefield" in the pharmaceutical industry — starting with the legendary story of the 1998 Ritonavir polymorph incident, and delve into the principles of FTIR distinguishing polymorphs, complementary applications with XRD/DSC, in-situ monitoring, and analytical methods for quantifying polymorph ratios.