Emerging and Established Methods for Acyclovir Quantification:

A Detailed Review

 

Diptimayee Jena, Satyabadi Sahoo, Pritam Mohanty, Debashis Mishra, Kirtimaya Mishra*

School of Pharmacy and Life Sciences, Centurion University of Technology and Management, Odisha.  

 

ABSTRACT:

Acyclovir (AVR), an antiviral drug often used to treat herpes simplex and varicella-zoster infections, necessitates precise and repeatable measurement for quality control, pharmacokinetic investigations, and therapeutic monitoring. This review examines both developing and known analytical approaches for determining AVR. Chromatography, spectrophotometry, electrochemical methods, and newer approaches, such as hyphenated and sensor-based methods, are critically evaluated as to sensitivity, accuracy, economical, and applicability across a wide range of dimensions. Analytical researchers often employ quality by design or design by expert techniques for improve method validation. Which make quick review that can help analysts select and validate the optimum analytical procedure. Recent innovations, such as nanotechnology-based sensors and green analytical techniques, are highlighted for their potential to improve detection capacities while also addressing environmental problems. The paper also looks at the limitations of established approaches and potential future paths for innovative analytical tools. This effort intends to help researchers and practitioners choose acceptable methodologies for AVR quantification, supporting improvements in antiviral medication analysis.

 

 

INTRODUCTION:

Antiviral drugs are a family of medications that are primarily used to treat viral infections. Antiviral medications treat viral illnesses. Viruses are significant pathogens responsible for numerous deadly diseases in humans, animals, and plants¹. Acyclovir (AVR) is an antiviral medication inured to control the signs and symptoms of infections brought on by the varicella-zoster virus (VZV) is the virus that causes the disease like shingles and chickenpox. VZV, which causes chickenpox and shingles, or the herpes simplex virus (HSV), which causes herpes simplex. AVR was found in the middle of the 1970s.  It works well against active, replicating VZV or HSV². Nucleoside analogues are widely used as antiviral medicines to treat HIV, HBV, HCV, CMV, HSV, and VZV. Reverse transcriptase inhibitors (NRTIs) are the conventional name for the nucleoside analogues used to treat HIV infection.  They work well against DNA polymerases that are reliant on RNA as well as DNA.  Through a variety of strategies, including as DNA chain termination and competitive inhibition of viral polymerase, they prevent the spread of viruses³.

 

 

 

Table 1 provides information about nucleoside analogues.

Drug	Structure	IUPAC Name	Molecular weight	Solubility
Abacavir		{(1S,4R)-4-[2-Amino-6-(cyclopropylamino)-9H-purin-9-yl]-2-cyclopenten-1-yl} methanol	322.79 g/mol	Easily dissolve dinmethanol, ethanol, andwater
Adefovir dipivoxil		2-(6-aminopurin-9-yl) ethoxymethylphosphonic acid	273.19 g/mol	Soluble in ethanol, methanol, water
Cidofovir-anhydrous		[(2S)-1-(4-amino-2-oxopyrimidin-1-yl)-3-hydroxypropan-2-yl] oxymethylphosphonic acid	279.19 g/mol	Solublein organic solvents such as ethanol, DMSO
AVR (Zovirax)		2-amino-9-(2- hydroxyethoxymethyl)-1H- purin-6-one	225.21 g/mol	Easily dissolved in ethanol andDSMO, minimally soluble in water
Entecavir (Baraclude)		2-amino-9-[(1S,3R,4S)-4- hydroxy-3-(hydroxy-methyl)-2- methylidene-cyclopentyl]-1H- purin-6-one	277.279g/mol	Easily dissolved in organic solvents like ethanol, DMSO, DMF and slightly soluble in water
Famciclovir (Famvir)		[2-(acetyloxy-methyl)-4-(2-amino-purin-9-yl)-butyl] acetate	321.332g/mol	Barely soluble in ethanol and isopropanol and freely soluble in acetone and methanol
Tenofovir anhydrous		[(2R)-1-(6-amino-purin-9-yl)-propan-2-yl]-oxymethyl-phosphonic acid	287.213g/ Mol	Soluble in DMSO, methanol, water and ethanol
Remdesivir (Veklury)		2-ethyl-butyl-(2S)-2-[[[(2R,3S,4R,5R)-5-(4-amino-pyrrole-[2,1-f][1,2,4]-triazin-7-yl)-5-cyano-3,4-dihydroxy-oxolan-2-yl]-methoxy-phenoxy-phosphoryl]-amino]-propanoate	602.585g/mol	Easily dissolved in organic solvents like ethanol, DMSO, DMF and lightly soluble in water
Sofosbuvir (Sovaldi)		(S)-Isopropyl2-((S)-(((2R,3R,4R,5R)-5-(2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl)-4-fluoro-3-hydroxy-4-methyltetrahydrofuran-2-yl) methoxy)-(phenoxy)phosphorylamino) propanoate	529.453g/mol	It is insoluble in heptane, soluble in 2-propanol, easily dissolve in ethanol and acetone, and slightly dissolved in water.

 

Acyclovir:

This dissertation briefly discusses acyclovir (AVR) among all the nucleoside analogue derivatives. AVR, or 2-amino-9-(2-hydroxyethoxymethyl)-1H-purin-6-one (Fig. 1), is an antiviral medication that belongs to the nucleoside analogues class. AVR triphosphate functions similarly to deoxyguanosine triphosphate (dGTP) in inhibiting viral Deoxyribose nucleic acid (DNA) polymerase. Because AVR triphosphate lacks a 3' hydroxyl group, which prevents more nucleosides from attaching, the chain ends when it is incorporated into DNA. AVR triphosphate has a high therapeutic ratio because it has a higher sensitivity for viral DNA polymerase than its biological counterpart^4-6.

 

 

Fig 1. Chemical Structure of Acyclovir

 

To provide a comprehensive review of the bioanalytical application of liquid chromatographic techniques coupled with mass spectrometry (LC/MS), a selection of the most relevant methods was compiled. This review starts with a brief introduction of the analytes and their main applications, followed by the description of LC-MS and LC-MS/MS methodologies from a practically and regulatory perspective. Because of the more pervasive/judicial use of drugs, special attention is paid to the sample extraction and analysis from plasma⁷.

 

Importance of Analytical Estimation:

Analytical method development and validation (AMDV) are found critical processes in pharmaceutical industry and other scientific fields, ensuring that analytical techniques are found to be robust, reliable, and suitable for their intended purposes in Table 1. This discussion highlights the importance of AMDV, its key components, and its implications for drug development and quality assurance^8-10.

 

Importance of Analytical Method Development:

·       Establishing Methodology:

Analytical method development involves creating and refining techniques to accurately measure and analyze the components of a product. This can include both the development of advanced methods and the improvement of existing ones. The aim is to established that the methods used was appropriate for the specific characteristics of the substances being tested, such as their identity, purity, potency, and stability^11-12.

 

·       Regulatory Compliance:

Validation of these methods is not just a best practice; it is a regulatory requirement. Regulatory authorities worldwide mandate that analytical methods used in clinical trials and for marketing authorization must be validated to demonstrate their accuracy, specificity, precision, and robustness. This is essential for gaining approval for new drugs and ensuring that they are safe and effective for patient use¹³.

 

·       Quality Assurance:

The reliability of analytical methods directly impacts the quality of pharmaceutical products. Validation establishes that a method consistently produces results that meet predefined criteria, which is vital for quality control and assurance throughout the drug development process. This includes assessing active pharmaceutical ingredients (APIs), excipients, and degradation products to ensure that they meet safety and efficacy         standards^14-15.

 

 

Key Components of Analytical Method Validation

Analytical method validation involves several critical parameters:

·       Accuracy: The closeness of the calculated quality to the observed value.

·       Precision: The degree to which repeated measurements identical findings are obtained from under unchanged conditions shows the same results.

·       Limit of Detection; LOD and Limit of Quantification; LOQ: The lowest analyte concentration that can be accurately measured or detected.

·       System Suitability Testing: Ensuring that the analytical system is operating correctly before analysis.

·       Specificity: The method's capacity to measure the analyte while additional analytes are present.

·       Robustness: The method's capacity to remain functional independently of small variations in method parameters.

 

Steps in Method Development and Validation:

·       Assessment of Existing Methods: Determine if current methods are sufficient or if new methods need to be developed.

·       Experimentation: Conduct experiments to test the new or improved methods against established standards.

·       Theory Application: Utilize theoretical frameworks to predict outcomes and analyze data.

·       Real-World Application: Apply the methods to actual samples to validate their effectiveness

 

 

 

 

Role in Pharmaceutical Industry:

The development and validation of advanced analytical methods act as an important role in the pharma industry, assuring that drugs are safe, effective, and of high quality. These processes are integral to the overall drug development lifecycle, from initial research through to clinical trials and manufacturing¹⁶. An overview of their significance, processes involved, and regulatory considerations is narrated below.

 

Regulatory Guidelines:

The validation of analytical methods and development is associated with guidelines established by various regulatory bodies. These include:

·       ICH Q2(R1): Provides guidelines for the validation of analytical procedures.

·       FDA Guideline for Industry: Outlines expectations for Validation of analytical techniques and processes for pharmaceuticals and biologics.

 

These guidelines help standardize the validation process across the industry, ensuring that all pharmaceutical products meet safety and efficacy standards.

 

Analytical Techniques for Estimation:

Pharmaceutical Analysis Techniques in figure 2:

The choice of analytical technique for estimation depends on the specific requirements of the project or analysis being conducted. Every approach has advantages and disadvantages, and frequently a mix of both of techniques is employed to achieve the most accurate and reliable results^17-18. Understanding these techniques is crucial for effective project management, data analysis, and pharmaceutical research in Tables 2 and 3.

 

 

Fig 2. Different techniques for Analysis

 

Chromatographic Techniques:

Table 2. Analysis between acyclovir and different drugs in different column with mobile phase

Sl. No	Column (Stationary Phase)	Mobile Phase (with ratio)	pH	Wavelength	Flowrate	Reference
Acyclovir with Curcumin
1	C18(250x4.6mm,5µm)	Mixture of acetonitrile,0.1%phosphoric acid, and methanol in the proportion of 50:40:10%v/v/v	-	254nm	0.8ml/min	19
Acyclovir with Hydrocortisone
2	C18(25x4.6 mm,5µm)	Mixture of Methanol: H2O in the proportion of 80:20%v/v	3	254nm	1ml/min	20
Acyclovir with Lidocaine
3	C18(250x4.6 mm,5µm)	Mixture of (20mM ammonium acetate in H2O and acetonitrile in the proportion of 95:5%v/v/v	3.5	254nm	1ml/min	21
Acyclovir Single Formulation
4	C18(250x4.6 mm,5µm)	Mixture of glacial acetic acid: acetonitrile Buffer in the proportion of 95:05 % v/v	3.8	253nm	1ml/min	22
5	C18(150x4.6 mm,5µm)	Mixture of H2O and acetonitrile, in the proportion of 95:05% v/v	-	254nm	0.8 ml/min	23
6	C-18,250mmx 4.6mm,5µ	Acetonitrile and pH-adjusted H2O in the proportion of 20:80% v/v	6.74	254nm	0.5 ml/min	24
7	C18(150x4.6 mm,3µm)	Mixture of H2O and acetonitrile in the proportion of 05:95% v/v	-	253nm	1ml/min	25
8	C18(75x4.6 mm,3.5µm)	Mixture of H2O and in the proportion of 95:05% v/v	-	254nm	1.9 ml/min	26
9	C18(150x3.9 mm,4µm)	Mixture of H2O and acetonitrile in the proportion of 78:22% v/v	-	254nm	0.8 ml/min	27
10	C8(4.6x1.5 mm,5µm)	Mixture of Acetonitrile and in the proportion of 70:30% v/v	3	254nm	0.5 ml/min	28
11	C18(150x4.6 mm,5µm)	Mixture of Acetonitrile: Methanol: Phosphate buffer: Acetonitrile in the proportion of 16:20:64% v/v	6	290nm	1ml/min	29
12	C18(150x4.6 mm,5µm)	Mixture of phosphate buffer and Methanol in the proportion of 95:05% v/v	2.5	254nm	1ml/min	30
13	C18(250x4.6mm5µm)	Mixture of 5 mM ammonium acetate andAcetonitrile, in the proportion of 40:60%v/v	4	290nm	1ml/min	31
14	C18(250x4.6 mm,5µm)	Mixture of HPLC-grade H2O andMethanol in the proportion of 50:50%v/v	-	250nm	1ml/min	32

 

Spectroscopic Techniques:

Table 3.  Determination of stability methods

Sl. No	Drug	Method	Description	Reference
1	Stability-Indicating Method Development and Validation of a UV Method for the Determination of Tablets of AVR in Solid dosage Form	Spectroscopic Method	Detection wavelength: 252 nm in 0.1N Sodium Hydroxide Linearity range: 5- 30 µg/ml Co-relation Coefficient: 0.999 %Recovery:99.72% %RSD: ≤2%	33
2	UV Spectrophotometric Analysis and Validation of AVR in Solid Dosage Form	Spectroscopic Method	Detection wavelength: 254nm in 0.2 Water Linearity range: 5- 30 µg/ml Co-relation Coefficient: 0.999 %Recoveryrange:100.1-100.5% %RSD: ≤2%	34

 

Applications of Analytical Tools in Drug Development:

Analytical tools play a crucial role in drug development, enhancing various stages from discovery to clinical trials. This overview highlights key applications of analytical methods and technologies in the pharmaceutical industry³⁵.

 

 

 

 

Applications of Analytical Tools in Drug Development:

A.   ML; Machine Learning andAI; Artificial Intelligence:

The implementation of artificial intelligence; AI and machine learning; ML algorithms in drug discovery and development procedures are expanding³⁶. These technologies facilitate in figure 3:

 

Fig 3. An analytical tool for technology facility

 

B. Analytical Method Development:

Analytical methods are vital for ensuring drug quality and safety. Key techniques include in Figure 4:

 

Fig 4.  Key techniques for analytical methods are vital for ensuring drug quality and safety.

 

C. Process Analytical Technology (PAT):

PAT is a methodology that enhances the quality and efficiency of pharmaceutical manufacturing. It involves in figure 5:

 

Fig 5. Enhances the quality and efficiency of pharmaceutical manufacturing

 

D. Data Analytics:

Pharmaceutical companies leverage data analytics to inform various aspects of drug development in figure 6:

 

Fig 6. Leverage data analytics to inform various aspects for drug development

 

E. Quality Control and Compliance

Ensuring compliance with stringent regulatory standards is paramount in drug development. Analytical tools help in figure 7:

 

Fig 7. Stringent regulatory standards are paramount in drug development

 

Formulation Development:

Importance of Analytical Method Validation in Formulation Development

·       Ensuring Drug Quality: The initial goal of any development program of pharmaceutical industries is to produce high-quality outcomes. Analytical method validation helps in understanding the composition of chemical compounds, which is crucial for the development of new drugs^37-38. This process allows for the identification of critical attributes that affect the drug's efficacy and safety.

·       Regulatory Compliance: Regulatory authorities, such as the FDA and EMA, require that analytical methods be validated before they can be used in clinical trials or marketed. A poorly documented chemistry, manufacturing, and controls (CMC) section can hinder the approval process for clinical trials^{39- 41}. Thus, having validated analytical methods simplifies regulatory compliance and provides clear information about the drug's quality.

·       Patient Safety: Patient safety is paramount in drug development. Analytical methods ensure that only safe compounds are used in clinical trials, which is essential for protecting human subjects during early-phase studies^42-44. The validation of these methods helps guarantee that the drugs administered are of the highest quality and efficacy.

 

Steps in Analytical Method Validation:

The validation procedure for analytical methods typically involves several key steps in figure 8:

 

Fig 8. Validation procedure for analytical methods

 

Challenges and Future Perspectives:

A. Challenges:

Complexity of Drug Formulations:

The intricate nature of pharmaceutical formulations, which often include multiple active ingredients and excipients, complicates the analytical method development process. This complexity can lead to issues with specificity and sensitivity, making it difficult to accurately quantify the active pharmaceutical ingredients (APIs) like AVR^45-47.

 

Regulatory Compliance:

Adhering to stringent regulatory requirements set by organizations such as the FDA and ICH is a vital guideline. The advancing of nature of these regulations necessitates continuous updates to analytical methods to ensure compliance, which can be resource-intensive.

 

Method Transfer and Validation:

The transfer of methods from research and development (RandD) to quality control (QC) labs can introduce variability. Ensuring that analytical methods maintain their performance across different settings is crucial but often problematic⁴⁸. This requires thorough validation processes that can be time-consuming and costly.

 

Technological Limitations:

While advancements in analytical instrumentation (e.g., UHPLC, MS) have improved the capabilities of analytical methods, there are still limitations regarding the sensitivity and specificity of these techniques when applied to complex biological matrice⁴⁹. This can hinder the detection of low-level impurities or degradation products in formulations.

 

Sample Preparation Challenges:

The need for efficient sample preparation techniques that minimize matrix effects while maximizing recovery of the analytes is paramount. Inadequate sample preparation can lead to inaccurate results, necessitating further method optimization^50-51.

B. Future Perspectives:

Integration of Advanced Technologies:

Future developments in analytical methods may increasingly rely on the integration of futuristic technologies such as AI and ML. These technologies can optimize method development processes, enhance data analysis, and improve the predictability of method performance⁵².

 

Focus on Robustness and Flexibility:

There is a growing emphasis on developing robust analytical methods that can withstand variations in sample composition and analytical conditions. This includes adopting systematic approaches to evaluate method robustness, such as design of experiments (DoE) methodologies, which can provide insights into how method parameters affect performance^53-54.

 

Regulatory Evolution:

As regulatory frameworks evolve, there will be a need for continuous education and adaptation of analytical methods to meet new guidelines. This includes a focus on the validation of methods for biopharmaceuticals, which may require different considerations compared to traditional small-molecule drugs^55-56.

 

Collaboration Across Disciplines:

Enhanced collaboration between analytical chemists, formulation scientists, and regulatory affairs professionals will be essential. This interdisciplinary approach can facilitate the development of more effective and compliant analytical methods that are aligned with the overall drug development strategy^57-60.

 

Sustainability Considerations:

The future of analytical method development will likely include a focus on sustainability, with an emphasis on reducing waste and energy consumption in analytical processes. This aligns with broader industry trends toward environmentally responsible practices in pharmaceutical development.

 

CONCLUSION:

In conclusion, while the challenges in developing and validating analytical methods for AVR are significant, the future holds promising advancements that can enhance the efficiency, accuracy, and compliance of these processes. Continuous innovation and collaboration will be key to overcoming existing hurdles and meeting the demands of the pharmaceutical industry.

 

ABBREVIATION:

AVR: Acyclovir

VZV: varicella-zoster virus

HSV: herpes simplex virus

LC/MS: liquid chromatographic techniques coupled with mass spectrometry

AMDV: Analytical method development and validation

LOD: Limit of Detection

LOQ: Limit of Quantification

ML: Machine Learning

AI: Artificial Intelligence

CMC: chemistry, manufacturing, and controls

APIs: active pharmaceutical ingredients

RandD: research and development

QC: quality control

 

CONFLICT OF INTERESTS:

The authors admitted that there is no conflict of interest between the authors.

 

ACKNOWLEDGEMENT:

The authors are thankful to Centurion University of Technology and Management for providing the necessary infrastructure for the research work. We are also thankful to our society for its positive attitude.

 

REFERENCE:

1.      Kausar S. Khan FS. Rehman MIM. Akram M. Riaz M. Rasool G. Khan AH. Saleem I. Shamim S. Malik A. A review: Mechanism of action of antiviral drugs. International Journal of Immunopathology and Pharmacology. 2021; 35: 1–12. doi: 10.1177/20587384211002621.

2.      Mishra K. Padmasri B. Vegesna S. Jabeen A. Dash A. Kumar S. Jena D. Chemometric Assisted UV-Spectrophotometric Quantification of Cefaclor in Suspension Dosage Form. International Journal of Pharmaceutical Quality Assurance. 2023; 14(3): 734-739.

3.      Seley-Radtke KL. Yates MK. The evolution of nucleoside analogue antivirals: A review for chemists and non-chemists. Part 1: Early structural modifications to the nucleoside scaffold, Antiviral Research. 2018; 154: 66–86.doi: 10.1016/j.antiviral.2018.04.004.

4.      Whitley RJ. Gnann JW Jr. Acyclovir: A decade later, New England Journal of Medicine. 1992; 327(11): 782-9. doi: 10.1056/NEJM199209103271108.

5.      Sharma S. goyal S. Chauhan K. A review on analytical method development and validation. International Journal of Applied Pharmaceutics. 2018; 10(6): 8-15. doi: http://dx.doi.org/10.22159/ijap.2018v10i6.28279.

6.      Rina R. Baile M. Jain A. A Review: Analytical Method Development and Validation, Systematic Reviews in Pharmacy. 2021; 12(8):450-454

7.      Mishra K. Sahoo S. Mahato P. Singh NK. Jena D. Advancing Azelnidipine Dosage Form Analysis: A Quality by Design Guided Journey with Green Chemistry Innovations. African Journal of Biological Sciences. 2024; 6(11): 423-434.

8.      Gowthami PRS. Rao GD. A review on analytical method development. Indian Journal of Research in Pharmacy and Biotechnology. 2014; 2(3): 1183-1195

9.      Mishra K. Jena D. Nayak NB. Jabeen A. Dash A. Sahoo S. Jena D. Advanced, Simple, Sensitive, Selective Reverse Phase Liquid Chromatography Technique for The Quantitative Determination of Ritonavir and Lopinavir in In-House Dosage Form. Bulletin of Environment, Pharmacology and Life Sciences. 2023; 12(11): 217-222.

10.   Sharma S. Singh N. Ankalgi AD. Rana A. Ashawat MS. Modern Trends in Analytical Techniques for Method Development and Validation of Pharmaceuticals: A Review. Journal of Drug Delivery and Therapeutics. 2021; 11(1-s): 121-130 doi: http://dx.doi.org/10.22270/jddt.v11i1-s.4515

11.   Verch T. Campa C. Cyrille C. Frenkel CR. Graul T. Jaya N. Nakhle B. et al. Analytical Quality by Design, Life Cycle Management, and Method Control. The American Association of Pharmaceutical Scientists. 2022; 24(1): 34. doi: 10.1208/s12248-022-00685-2.

12.   Lal B. Kapoor DU. Jaimini M. A review on analytical method validation and its regulatory perspectives. Journal of Drug Delivery and Therapeutics.2019; 9(2): 501-506. doi:10.22270/jddt. v9i2.2403.

13.   Siddiqui MR. Zeid A. Rahman AN. Analytical techniques in pharmaceutical analysis: A review. Arabian Journal of Chemistry. 2017; 10:  S1409–S1421

14.    Kim EJ. Kim JH. Kim MS. Jeong SH. Choi DH. Process Analytical Technology Tools for Monitoring Pharmaceutical Unit Operations: A Control Strategy for Continuous Process Verification. Pharmaceutics. 2021; 13(6): 919. doi: 10.3390/pharmaceutics13060919

15.   Badgujar VM. Jain PS. Advances in Analytical Techniques, Method Development, And Validation Protocols in Pharmaceutical Research, International Journal of Pharmaceutical Sciences. 2024; 2(3): 728-738. doi: https://doi.org/10.5281/zenodo.10845542

16.    Mishra P. Pandey CM. Singh U. Keshri A. Sabaretnam M. Selection of appropriate statistical methods for data analysis. Annals of Cardiac Anaesthesi. 2019; 22: 297-301.

17.   Munteanu IG. Apetrei C. Analytical Methods Used in Determining Antioxidant Activity: A Review. International Journal of Molecular Sciences. 2021; 22(7): 3380. doi: 10.3390/ijms22073380.

18.   Shabir GA. Validation of high-performance liquid chromatography methods for pharmaceutical analysis: Understanding the differences and similarities between validation requirements of the US Food and Drug Administration, the US Pharmacopeia and the International Conference on Harmonization. Journal of Chromatography A. 2003; 987(1–2): 57-66

19.   Reolon J. Brustolin M. Haas SE. Bender EA. Malesuik MD. Colome LM. Development and validation of high-performance liquid chromatography method for the simultaneous determination of acyclovir and curcumin in polymeric microparticles. Journal of Applied Pharmaceutical Science. 2018; 8(1): 136-141.

20.   Naik RM. Ahmed S. Reddy GNK. RP-HPLC Method Development and Validation for Simultaneous Estimation of Hydrocortisone and Acyclovir in Pharmaceutical Dosage Forms. American Journal of Pharmacy and Health Research. 2018; 6(6): 5-18.

21.   Mulabagal V. Annaji M. Kurapati S. Dash RP. Srinivas NR. Tiwari AK. Babu RJ. Stability-indicating HPLC method for acyclovir and lidocaine in topical formulations. Biomedical Chromatography. 2020; 34(3): e4751.doi: 10.1002/bmc.4751. Epub 2020 Jan 12.

22.   Kumar YP. Sreedhar C.  Rao ST.  Akkamma HG.  Reddy GB.  Shrestha DM. New Analytical Method Development and Validation of Acyclovir by Rp-Hplc Method. Unique Journal of Pharmaceutical and Biological Sciences. 2016; 4(2):20-26.

23.   Stulzer HK. Tagliari MP. Murakami FS. Silva MAS. Laranjeira MCM. Development and Validation of an RP-HPLC Method to Quantitate Acyclovir in Cross-Linked Chitosan Microspheres Produced by Spray Drying. Journal of Chromatographic Science. 2008; 46: 496-500.

24.   Ghumre SV. Jadhav VM. Kadam VJ. High Pressure Liquid Chromatographic Method Development andValidationfor Estimation of Acyclovir in Bulk and Marketed Formulation. International Journal of Pharmaceutical Sciences and Research. 2016; 7(5): 2194-2200.

25.   Hamdi A. Fegast R. Berka B. Clarck BJ. Stability test of Acyclovir at severe conditions. Asian Journal of Chemistry. 2005 17(4): 2699-2704.

26.   Quadeib BTA. A simple RP-HPLC method for Acyclovir determination in tablet and cream dosage forms. Drug Discovery. 2019; 13:107-114.

27.   Ghosh S. Sahu A. Kumar DS. Jena S. Harani A. Reddy TPK. Tanuja D. Method development and validation for acyclovir in tablet dosage form by RP-HPLC. Journal of Pharmacy Research. 2012; 5(3): 1785-1786.

28.   Mule SG. Patre NG. Kshirsagar AD. Kharwade SB. The Estimation of Acyclovir in Bulk and Tablet Dosage form by Using Specificity and Analytical Method Development. Acta Scientific Pharmaceutical Sciences. 2022; 6(3): 9-12.

29.   Manoharan G. Mohamed RAW. Development and Validation of a Stability-Indicating RP-HPLC Method for the Estimation of Aciclovir in Bulk and Ointment Dosage Form. International Journal of Pharmaceutical and Phytopharmacological Research. 2019;  9(1): 11-18.

30.   Kumar CV. Kumar DA. Rao JVLNS. Development and Validation of Rp-Hplc Method for the Determination of Acyclovir in Human Plasma. International Journal of Chemical Science. 2010; 8(1): 475-482.

31.   Muralidharan S. Kalaimani J. Parasuraman S. Dhanaraj SA. Development and Validation of Acyclovir HPLC External Standard Method in Human Plasma: Application to Pharmacokinetic Studies. Advances in Pharmaceutics. 2014; 1-5.

32.   Ravisankar P. Niharika A. Sireesha S. Koushik OS. Himaja V. Development and Validation of Rp-Hplc Method for Quantitative Estimation of Acyclovir in Bulk Drug and Tablets. Journal of Chemical and Pharmaceutical Sciences. 2015; 8(1): 73-80

33.   Dessai P. FatrekarN. Stability Indicating Method Developmnt and Validation of Uv Method for the Determination of Acyclovir in Tablet Dosage Form. Indo American Journal of Pharmaceutical Sciences. 2018; 5(9): 8955-8960.

34.   Lasure A. Ansari A. Kalshetti M. UV Spectrophotometric Analysis and Validation of Acyclovir in Solid Dosage Form, International Journal of Current Pharmaceutical Research. 2020; 12(2): 100-103

35.   Paul D. Sanap G. Shenoy S. Kalyane D. Kalia K. Tekade RK. Artificial intelligence in drug discovery and development. Drug Discovery Today. 2021; 26(1): 80-93. doi: 10.1016/j.drudis.2020.10.010

36.    Jang IJ. Artificial intelligence in drug development: clinical pharmacologist perspective. Translational and Clinical Pharmacology. 2019; 27(3): 87-88. doi: 10.12793/tcp.2019.27.3.87.

37.    Hughes JP. Rees S. Kalindjian SB. Philpott KL. Principles of early drug discovery. British Journal of Pharmacology. 2011; 162(6): 1239-49. doi: 10.1111/j.1476-5381.2010. 01127.x

38.    Pramod K. Tahir MA. Charoo NA. Ansari SH. Ali J. Pharmaceutical product development: A quality by design approach. International Journal of Pharmaceutical Investigation. 2016; 6(3): 129-38. doi: 10.4103/2230-973X.187350

39.    Popkin ME. Goese M. Wilkinson D. Finnie S. Flanagan T. Campa C. Clinch A. Teasdale A. Lennard A. Cook G. Mohan G. Osborne MD. Chemistry Manufacturing and Controls Development. Industry Reflections on Manufacture, and Supply of Pandemic Therapies and Vaccines. American Association of Pharmaceutical Scientists. 2022; 24(6): 101. doi: 10.1208/s12248-022-00751-9

40.    Algorri M. Cauchon NS. Abernathy MJ. Transitioning Chemistry, Manufacturing, and Controls Content with a Structured Data Management Solution: Streamlining Regulatory Submissions. Journal of Pharmaceutical Sciences. 2020; 109(4):1427-1438

41.   Chiodin D. Cox EM. Edmund AV. Kratz E. Lockwood SH. Regulatory Affairs 101: Introduction to Investigational New Drug Applications and Clinical Trial Applications. Clinical and Translational Science. 2019; 12(4): 334-342. doi: 10.1111/cts.12635.

42.    Samara C. Garcia A. Henry C. Vallotton L. Cariolato L. Desmeules J. Pincon A. Safety Surveillance During Drug Development: Comparative Evaluation of Existing Regulations. Advances in Therapy. 2023; 40(5):2147-2185. doi: 10.1007/s12325-023-02492-3.

43.    Yao B. Zhu L. Jiang Q. Xia HA. Safety monitoring in clinical trials. Pharmaceutics. 2013; 5(1): 94-106. doi: 10.3390/pharmaceutics5010094

44.   Krishnan B. Mishra K. Quality by Design based Development and Validation of RP-HPLC Method for Simultaneous Estimation of Sitagliptin and Metformin in Bulk and Pharmaceutical Dosage Forms. International Journal of Pharmaceutical Investigation. 2020; 10(4): 512-518.

45.   Buckley LA. Bebenek I. Cornwell PD.  Hodowanec A. Jensen EC. Murphy C. Ghantous HN. Drug Development 101: A Primer. International Journal of Toxicology. 2020; 39(5): 365-495

46.   Balamurugan K. Mishra K. Optimization and Validation of the Simultaneous Determination of Vildagliptin and Metformin, in Bulk and Formulation by A Reverse Phase HPLC Method Using D-Optimal Experimental Design. Journal of Global Pharma Technology. 2020; 12(8):1-12.

47.    Azadeh M. Sondag P. Wang Y. Raines M. Sailstad J. Quality Controls in Ligand Binding Assays: Recommendations and Best Practices for Preparation, Qualification, Maintenance of Lot-to-Lot Consistency, and Prevention of Assay Drift. American Association of Pharmaceutical Scientists. 2019; 21(5): 89. doi: 10.1208/s12248-019-0354-6

48.    Song JG. Baral KC. Kim GL. Park JW. Seo SH. Kim DH. Jung DH. Ifekpolugo NL. Han HK. Quantitative analysis of therapeutic proteins in biological fluids: recent advancement in analytical techniques. Drug Delivery. 2023; 30(1): 2183816. doi: 10.1080/10717544.2023.2183816

49.   Reddy MR. Mishra K. Suresh R. Development and Validation of a Liquid Chromatographic Method for the Determination of Selected Anti Cancer Drugs in Bulk and Pharmaceutical Formulations. International Journal of Pharma Research and Health Sciences. 2018; 6(1): 2303-07.

50.    Cortese M. Gigliobianco MR. Magnoni F. Censi R. di Martino PD. Compensate for or Minimize Matrix Effects? Strategies for Overcoming Matrix Effects in Liquid Chromatography-Mass Spectrometry Technique: A Tutorial Review. Molecules. 2020; 25(13): 3047. doi: 10.3390/molecules25133047

51.   Clark KD. Zhang C. Anderson JL. Sample Preparation for Bioanalytical and Pharmaceutical Analysis. Analytical chemistry. 2016; 88(23): 11262-11270.

52.   Dwivedi YK. Sharma A. Rana NP. Giannakis M. Goel P. Dutot V. Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions. Technological Forecasting and Social Change. 2023; 192: 122579.

53.   Park G. Kim MK. Go SH. Choi M. Jang YP. Analytical Quality by Design (AQbD) Approach to the Development of Analytical Procedures for Medicinal Plants. Plants (Basel). 2022; 11(21): 2960. doi: 10.3390/plants11212960

54.    Sangshetti JN. Deshpande M. Zaheer Z. Shinde DB. Arote R. Quality by design approach: Regulatory need. Arabian Journal of Chemistry. 2017; 10(supplement 2): S3412-S3425

55.    Gutierrez L. Cauchon NS. Christian TR. Giffin MJ. Abernathy MJ. The Confluence of Innovation in Therapeutics and Regulation: Recent CMC Considerations. Journal of Pharmaceutical Sciences. 2020; 109(12): 3524-3534. doi: 10.1016/j.xphs.2020.09.025

56.    Nupur N. Joshi S. Gulliarme D. Rathore AS. Analytical Similarity Assessment of Biosimilars: Global Regulatory Landscape, Recent Studies and Major Advancements in Orthogonal Platforms. Frontiers in Bioengineering and Biotechnology. 2022; 10: 832059. doi: 10.3389/fbioe.2022.832059

57.   Vora LK. Gholap AD. Jetha K. Thakur RRS. Solanki HK. Chavda VP. Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design. Pharmaceutics. 2023; 15(7):1916. doi: 10.3390/pharmaceutics15071916

58.   Kapustina O. Burmakina P. Gubina N. Serov N. Vinogradov V. User-friendly and industry-integrated AI for medicinal chemists and pharmaceuticals. Artificial Intelligence Chemistry. 2024; 2(2): 100072

59.   Sampene AK. Nyirenda F. Evaluating the effect of artificial intelligence on pharmaceutical product and drug discovery in China. Future Journal of Pharmaceutical Sciences. 2024; 10: 58. https://doi.org/10.1186/s43094-024-00632-2

60.   Yin L. Yu L. Guo Y. Wang C. Ge Y. Zheng X. Zhang N. You J. Zhang Y. Shi M. Green analytical chemistry metrics for evaluating the greenness of analytical procedures. Journal of Pharmaceutical Analysis.  2024; 14(11): 101013

 

 

 

 

Received on 15.05.2025      Revised on 24.06.2025 Accepted on 28.07.2025      Published on 04.10.2025 Available online from October 10, 2025 Asian J. Res. Pharm. Sci. 2025; 15(4):409-417. DOI: 10.52711/2231-5659.2025.00061 ©Asian Pharma Press All Right Reserved
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