Drug Repurposing: A Leading Strategy for New Threats and Targets

Abstract

Less than 6% of rare illnesses have an appropriate treatment option. Repurposed medications for new indications are a cost-effective and time-saving strategy that results in excellent success rates, which may significantly lower the risk associated with therapeutic development for rare illnesses. It is becoming a realistic alternative to repurposing “conventional” medications to treat joint and rare diseases considering the significant failure rates, high expenses, and sluggish stride of innovative medication advancement. This is due to delisted compounds, cheaper research fees, and faster development time frames. Repurposed drug competitors have been developed using strategic decisions based on data analysis, interpretation, and investigational approaches, but technical and regulatory restrictions must also be considered. Combining experimental and computational methodologies generates innovative new medicinal applications. It is a one-of-a-kind strategy for repurposing human-safe pharmaceuticals to treat uncommon and difficult-to-treat ailments. It is a very effective method for discovering and creating novel medications. Several pharmaceutical firms have developed novel therapies by repositioning old medications. Repurposing drugs is practical, cost-effective, and speedy and generally involves lower risks when compared to developing a new drug from the beginning.

“Conventional” medications are being repurposed due to high attrition rates and expensive and sluggish pharmaceutical development and advancement. DEREK predicted compounds might lower expenses.¹ DEREK is a computer-based expert system that can predict the toxicity of compounds. Several data-driven and experimental repurposing methods are outlined. Despite advancements in technology and medicine, the progress in therapeutics for newly invented drugs remains uncertain. Additionally, factors such as high attrition rates, delayed drug launches, and evolving regulatory constraints can lead to increased costs.^2,3 Investing in pharmaceuticals is considered unwise due to the increasing costs and extended timelines associated with developing new drugs. Repurposing drugs requires new therapeutic uses, and alternative drugs are repurposed.⁴ Pharmaceutical repositioning focuses on rare diseases, utilizing existing drugs to enhance output, profits, and savings. These drugs, whether originally intended for different purposes, may have effects either aligned or not aligned with their intended targets, introducing alternative or multipurpose medication.⁵ Drug repurposing lacked a systematic approach until Pfizer repurposed Sildenafil as Viagra in 2012, generating $2.05 billion in revenue. Thalidomide, introduced in 1957, was withdrawn in 1961 due to its link to first-trimester bone deformities, leading to its prohibition during pregnancy.⁶⁻⁸ Myeloma and ENL1 were treated after 1964.⁸ Revlimid (lenalidomide), a drug used to treat multiple myeloma and certain anemias, saw a 2.08% increase in global sales in 2022, reaching $10,057 million. However, revenues dropped significantly after the generic version was launched in March 2022, affecting Celgene’s revenue. Most repurposing uses pharmacology or retrospective studies (Table 1). To repurpose a drug is to discover novel applications for it. Rare medications are frequently reassigned. By extending the indication or repositioning pharmaceuticals, it is feasible to secure expedited, cost-effective approval for innovative therapies that solve unfulfilled medical requirements and provide significant commercial and clinical advantages.⁹ Medication repositioning increases effectiveness and decreases failure rates through the development of novel applications that benefit society. The purpose of the experiment and repurposed medication are controversial. Box 1 (Glossary 1) displays Directive 2001/83/EC Articles 6, 8, 3, 10, 3, and 5.^10,11 Due to the limited patent protection for repurposed generic medications, rare disease regulation is critical, as fewer than 200,000 Americans suffer from rare illnesses.¹² 236 treatments for rare diseases are not commercially available, per the FDA (Table 2). Drug repositioning, a method that involves de novo drug discovery, saves time, money, and risk by accelerating R&D, reducing the need for preclinical testing, clinical trials, approval, marketing, and post-approval safety monitoring. Repurposing includes chemical discovery, procurement, development, and postmarket safety monitoring¹³ (Figure 2). The suggested treatment is supported by preclinical and clinical data in the field of pharmacological repurposing. The numerous advantages of repurposed medications for the treatment of intractable infections are illustrated in Figure 1.¹⁴⁻¹⁶ This review explores the positive aspects of drug repurposing in the creation of different formulations and drugs for fatal diseases, in contrast to the tedious and time-consuming method of discovering new drugs. This research investigates several approaches used in the repurposing of medications and explores the challenges found in the conventional approach and the advantages linked to pharmaceutical repurposing. Pharmaceutical repurposing offers validation for pharmaceutical compounds now undergoing development as well as those that have already undergone repurposing and are also in the developmental stage. The obstacles pertaining to repurposing are also highlighted with a variety of ethical considerations. A thorough examination of the computational method and experimental approach has been provided. The primary objective of this research is to undertake a thorough examination of the various strategies used in the repurposing of medications with a special emphasis on the application of computational tools. Furthermore, our firm provides catalogs that allow quick accessibility to research pertaining to the repurposing of medications. Moreover, extensive deliberations on prospective developments have been undertaken.

Table 1. Illustrations of Effective Pharmaceutical Repurposing and the Applicable Repurposing Technique^a.

Drug Name	Indigenous Sign	Novel Sign	Date of Endorsement	Repurposing Approach Used	Explanations of the Consequence of Repurposing	Ref.
Zidovudine	Carcinoma	Acquired immunodeficiency syndrome	1987	In vitro run of chemical library compounds	The FDA originally authorized (approved) zidovudine as an anti-HIV medication.	(17)
Minoxidil	Hypertension	Alopecia	1988	Clinical evaluation of the past (documentation of hair development as an antagonistic effect)	2016 saw universal sales of $860 million for minoxidil.	(18)
Sildenafil	Angina pectoris	Impotence	1998	Clinical evaluation of the past	With sales of $2.05 billion worldwide in 2012, sildenafil, marketed as Viagra, dominated the market for erectile dysfunction drugs.	(19)
Thalidomide	Hyperemesis gravidarum	Erythema nodosum leprosum and Kahler disease	1998 and 2006	Utilization of off-label and pharmacologic assessment	Treating multiple myeloma with thalidomide derivatives has achieved significant clinical and economic success.	(20, 21)
Celecoxib	Discomfort and redness	Familial adenomatous polyps	2000	Analytical pharmacology	Celexa (Pfizer) had total sales of $2.70 billion at the end of 2014.	(22)
Atomoxetine	Parkinson disease	ADHD	2002	Analytical pharmacology	In 2016, Strattera (Eli Lilly) had worldwide sales of $856 million.	(23)
Duloxetine	Depression	SUI	2004	Analytical pharmacology	The EMA has approved its usage in SUI. In the United States, the application was revoked. The FDA has authorized (approved) duloxetine to treat chronic pain and depression in the United States.	(24)
Rituximab	Various cancers	Rheumatoid arthritis	2006	A review of old medical records (reduction of concomitant rheumatoid arthritis in individuals treated with rituximab for non-Hodgkin lymphoma)	In 2015, worldwide sales of rituximab surpassed $7 billion.	(25, 26)
Raloxifene	Osteoporosis	Breast cancer	2007	Clinical evaluation of the past	FDA-approved aimed at breast cancer that has spread. 2015 global sales amounted to $237 million.	(27)
Fingolimod	Transplant rejection	MS	2010	Analyses of pharmacology and structure	For multiple sclerosis, the principal oral disease-modifying therapy has been approved. Fingolimod (Gilenya) had a $3.1 billion worldwide market in 2017.	(28)
Dapoxetine	Analgesia and depression	Premature ejaculation	2012	Analytical pharmacology	Europe and the United Kingdom are among the nations where it is legal; US clearance is forthcoming. Peak sales of more than $750 million are anticipated.	(29)
Topiramate	Epilepsy	Obesity	2012	Analytical pharmacology	Qsymia (Virus) is composed of topiramate and phentermine.	(30)
Ketoconazole	Fungal infections	Cushing syndrome	2014	Pharmacologic investigation	Topiramate and phentermine are present in Qsymia (Virus).	(31)
Aspirin	Analgesia	Colorectal cancer	2015	Clinical and pharmaceutical review of the past	Clinical and pharmaceutical analysis in retrospect	(32)

^aDespite legal and economic obstacles, a handful of recent successes have proved the public health advantages and commercial value of pharmaceutical repositioning. The first examples of effectively relocated medications are acetylsalicylic acid, thalidomide, sildenafil,¹⁹ and dimethyl fumarate.

Box 1. Glossary 1: Difficulties with Big Data.

Medicine, biology, and biotechnology support the research-driven healthcare industry. Computational and data-driven disciplines are becoming more critical in an industry that handles large amounts of data. Biological big data for translational and healthcare research must be clean, well-organized, annotated, classed, correlated, and integrated. More data silos require organization and cleanliness. Clinicians must prepare for IoP to replace IoT. Precision medicine needs EHRs and data (both clinical and molecular). Drug repurposing and physiology tool development are crucial. Researchers can collect massive amounts of experimental data due to next-generation sequencing and falling prices.⁴⁴ DNA and RNA sequencing data include phenotyping, MS, metabolomics, and transcriptomics. This data pool is growing. Knowledge sources include clinical trials, biobanks, and EHRs. Big data are large or complex fact collections. Inadequate data processing existed. Complex and diverse biomedical data are proportional to the number of available metrics.⁴⁵ Genomes, transcriptomics, proteomics, tissue/single-cell specificity, imaging, and clinical evaluation provide data. Physiological indicators of health, illness, and individuality make up the biological phenotypic layer. Large amounts of data are not magical, so they’re useless. Knowledge that is explicit, comprehensible, innovative, and valuable must be derived from data. Before sharing, information must be filtered and quality-checked. A 2017 UW presentation discussed how not to handle big data. “Big data arrogance” is cautioned.^46,47

Table 2. Some Accessible Strategies for Medication Repositioning^a.

Procedure	Methodological Category	Technique/Precise Procedure	Illustration(s)
Drug-Intended
Phenotypic screening	Screening that is blind/target-based	HTS/HCS in vivo and in vitro screening	Sildenafil (erectile dysfunction), rituximab (breast cancer)
The target’s three-dimensional structure, as well as information on the medicines and ligands that interact with it	Target-specific cheminformatics	Ligand detection, docking, and fragment screening are used in silico.	Fluorouracil (lung cancer), etoposide (bladder cancer)
Pharmacological structure, target, and drug data and drug–target information	Bioinformatics/cheminformatics-based	Drug–target anticipation	Simvastatin, ketoconazole (breast cancer)
Information about clinical trials and adversative consequences	Bioinformatics, a science based on knowledge	Medication resemblance studies	—
FDA approval labels	Knowledge-based, bioinformatics	Drug resemblance studies	—
Disease-Intended
Accessible trail evidence	Knowledge-based, bioinformatics	Disease processes and therapy targets are being identified and targeted.	Vismodegib (skin cancer)
Disease omics/genetics data	Bioinformatics based upon signatures	Using gene signatures and genomics to discover important targets	—
Disease omics information, accessible pathway evidence, and protein interaction network	Network biology is based on pathways or networks.	Identification of crucial targets by the method of course and network analysis unique to illness	Sunitinib, dasatinib (breast cancer, brain tumor)
Therapy-Intended
Drug omics information	Signature-based or signature-based and network-based bioinformatics	Gene signature research	Sirolimus (acute lymphocytic leukemia), Fasudil (neurodegeneration)
Disease omics and drug omics data	Bioinformatics using signatures	Resemblances among medications and illnesses	Cimetidine (lung cancer), topiramate (inflammatory bowel disease)
Drug omics information, the illness route, and the protein interaction network	Network, systems, and targeted-mechanistic biology	Clarifying specific paths	Daunorubicin, clomifene (ductal carcinoma)

^aBiochemical and experimental disease models and screenings can be blind or prescreened to identify unexpected results. These drug discovery approaches are more valuable because they can test for more medications and disorders.^50,54−56

Figure 2.

Drug repurposing and conventional drugs: a comparative analysis. The comparative study conducted between medication repurposing and traditional drug development elucidates significant disparities in the methodologies used in pharmaceutical research. The concept of drug repurposing, as examined within this framework, entails the identification of novel applications for pre-existing medications, in contrast to traditional drug discovery which primarily centers on the development of totally new chemical compounds for therapeutic purposes. The purpose of this comparative study is to highlight the benefits, drawbacks, and changing frameworks in the domain of pharmaceutical research and development. Ultimately, this analysis helps in making better-informed decisions and allocating resources more effectively in the quest for innovative therapeutic interventions.

Figure 1.

Illustration of the advantages of drug repurposing. Drug repurposing is a prominent approach used in the field of pharmaceutical research, whereby novel therapeutic applications for pre-existing medications are identified. The use of this approach has many notable benefits, including accelerated development processes, reduced risk factors, enhanced treatment possibilities, improved patient outcomes, sustainable practices, versatile applications, cost-effectiveness, and identification of synergistic combinations of pharmaceutical agents. Nevertheless, the industry has obstacles, such as the task of discerning appropriate people and maneuvering through regulatory processes for novel applications. Thorough assessment and scholarly investigation are required in order to effectively harness the potential advantages of pharmaceutical repurposing.

1. Drug Repurposing vs Conventional Drug Discovery

Previously, repurposing medications was opportunistic and serendipitous; commercial use was promoted until an off-target or on-target impact was shown. Historically, repurposing medications was opportunistic and serendipitous; a treatment was commercialized once its on-target or off-target effect was shown.³³ Sildenafil citrate, the active ingredient in Viagra, was developed through a retrospective experimentation. Viagra captured 47% of the market share, resulting in sales totaling $2.05 billion. The sedative thalidomide was taken off the market four years after it was licensed in a few countries because it caused severe bone congenital disabilities in infants born to women who took it during the first trimester. Multiple myeloma was diagnosed in 1984; ENL1 helped cure it in 1999. 2017 saw $8.2 billion in lenalidomide sales. Table 1 shows pharmacological repurposing examples and methods. FDA-approved or marketed treatments and innovative experimental therapies are repositioned (IND).⁸ Medications are also being repurposed for the treatment of COVID. Repurposing a drug seeks new uses. Goal: to make chemicals. It is a cutting-edge technique for “derisked” therapeutic chemicals and targets, speeding up drug development and saving money because the treatment can be created quickly and sold for more profit. Pharmaceutical repositioning has decreased the failure rate of medication development, and Figure 3 depicts the numerous ways and tactics for drug repositioning.^34,35 Thalidomide is a drug that is being abused and there is a controversial debate about repurposing it for potential societal improvement.^36,37Table 1 illustrates several instances of repositioned drugs.

Figure 3.

This diagram illustrates the many strategies for medication repurposing. The diagram shown clearly demonstrates the wide range of tactics used in the process of pharmaceutical repurposing. The comprehensive strategy involves a range of approaches such as computational drug screening, target-based repurposing, pathway analysis, and phenotypic screening, among other techniques. By elucidating various tactics, this map not only offers a full depiction of the drug repurposing terrain but also emphasizes the adaptability and ingenuity necessary for leveraging pre-existing medications for novel therapeutic objectives. This resource provides significant value to academics and stakeholders engaged in the investigation of repurposed pharmaceuticals as a potentially fruitful pathway in the field of drug discovery and development.

2. Approaches for Drug Repurposing

2.1. Challenges and Opportunities

Repurposing entails finding new applications for old drugs. Repurposed candidates are safer in animal and early-stage human research. Legal concerns might make it difficult to patent a further medical use or enforce patent rights, reducing the likelihood of pharmaceutical repurposing. Generic active components in compounds may pose health issues. Repurposing medication for uncommon and undertreated illnesses is cost-effective.

The pharmaceutical industry, patients with rare diseases, and research all benefit from the repurposing of antibiotics. Concerning rare diseases, neither the biology nor the pathophysiology are understood. As per the Orphan Medication Act of 1983, a record-breaking 75% of rare diseases do not have FDA-approved medications. Concern arose that a medicine for a rare disease would not generate sufficient revenue. The FDA has authorized 360 medications for rare illnesses since 1983. Fifty US laws expediting FDA approval, commercial fortification, tax advantages, and clinical research funding for uncommon disorders were enacted prior to 1983. Fexinidazole is the first oral drug to cure advanced sleeping sickness for 30 years. DNDi developed it for $62.5 million. Systems medicine/network pharmacology incorporates several drug-finding methods. One-third of FDA-approved drugs were previously used. Medication rescue uses outdated medication projects and pharmaceutical firm portfolios cost-effectively.

With the help of new business models, formerly isolated communities may work together. This involves private equity, government funding, and philanthropic organizations. Medications may be repositioned to save both money and time. Medication repositioning has been simplified with the use of computers. Drug administration is sped up using DR’s hybrid method. Profitability in treating rare or under-treated diseases may be possible. As the rate of failure is reduced, the development process is streamlined, and costs are reduced by reusing existing medications to treat both common and uncommon conditions; this area of research is exciting.^38,39 Researchers can access the most up-to-date and dependable resources to study disease-specific proteins, genes, and biomarkers. With the development of genomics, proteomics, transcriptomics, metabolomics, etc., and the availability of vast database resources such as medication omics data and illness omics data, there are many opportunities to identify pharmaceuticals by drug repositioning. Researchers now have access to the most up-to-date and exact tools and data for exploring undiscovered mechanisms of action and routes.^40,41 The public can access genomes, proteomics, and other databases and tools. There are several computational approaches. Table 6 lists some of the most popular databases for exploring pharmaceutical repositioning. They are designed to speed up and simplify the repurposing process.^42,43

Table 6. Repositioning Studies’ Catalogs^a.

Evidence Accessible about	Catalogs	Site
Chemical structure	PubChem	https://pubchem.ncbi.nlm.nih.gov/
	Drugbank	https://go.drugbank.com/
	Chemspider	http://www.chemspider.com/
	ChemDB	https://www.hugedomains.com/domain_profile.cfm?d=chemdb.com
	Therapeutic Target Database (TTD)	http://bidd.nus.edu.sg/group/cjttd/
Target 3D structure	RCSB Protein Statistics Bank (PDB)	https://www.rcsb.org/
	OCA	https://oca.weizmann.ac.il/oca-bin/ocamain
	Proteopedia	https://proteopedia.org/wiki/index.php/Main_Page
Drug–target evidence	Drug Bank	https://go.drugbank.com/
	Therapeutic Target Database (TTD)	https://db.idrblab.net/ttd/
	Pharmacogenetics Knowledge Base (PharmGKB)	https://www.pharmgkb.org
	Drug-Map Central (DMC)	https://drugcentral.org/
Protein interaction information	Human Protein Reference Database (HPRD)	https://www.hsls.pitt.edu/obrc/index.php?page=URL1055173331
	Biological General Repository for Interaction	https://thebiogrid.org/
	Database of Interacting Proteins (DIP)	https://ngdc.cncb.ac.cn/databasecommons/database/id/5254
	STRING	https://string-db.org/
Pathway information	NCI Pathway Interaction Database (NCI-PID)	https://wiki.nci.nih.gov/pages/viewpage.action?pageId=315491760
	Kyoto Encyclopedia of Genes and Genomes (KEGG)	https://www.genome.jp/kegg/
	Pathway Commons	http://www.pathwaycommons.org/about/
		https://www.pathwaycommons.org/
Information about clinical trials results and adverse consequences	Registry and results database of clinical studies	https://clinicaltrials.gov/
	https://www.intechopen.com/	https://www.fda.gov/Drugs/
	Adverse Effects Database (Canada)	http://sideeffects.embl.de/
	SIDER
FDA label information	FDA LABEL (US FDA)	https://labels.fda.gov/
	Daily Med (US FDA)	https://www.fda.gov/Science-Research
	Structured Product Labeling (SPL)	https://dailymed.nlm.nih.gov/dailymed/
		https://www.fda.gov/industry/fda-data-standards-advisory-board/structured-product-labeling-resources
		https://www.fda.gov/industry/fda-data-standards-advisory-board
Omics data (target/drug)	NCBI-GEO	https://www.ncbi.nlm.nih.gov/geo/
	Sequence Read Archive (SRA)	http://www.ncbi.nlm.nih.gov/Traces/sra/
	Array Express	https://www.ncbi.nlm.nih.gov/sra
	Cancer Cell Line Encyclopedia (CCLE)	https://www.ebi.ac.uk/arrayexpress/
		https://sites.broadinstitute.org/ccle/
		http://www.broadinstitute.org/ccle/home

^aDatabases are used for repositioning studies. Subsequently, their drug database encompasses the majority of FDA-approved medications for usage in the United States. In addition, you may search the FDA’s drug catalog for drugs that have complete human testing or are in the approval process.^131,132

3. Methods for Repurposing Drugs

DR approaches rely on pharmacologic, toxicologic, and biotic data. They emphasize medication, goals, or disease/treatment. The drug-focused analysis examines the structure, activity, side effects, and toxicity. This method finds bioactive compounds using cell and animal studies. This repositioning technique is based on conventional pharmacology and drug development, in which biological effects are evaluated without knowledge of biological targets. This orientation profile led to the discovery of sildenafil. After in silico or virtual high-throughput screening, HCS in vitro and in vivo screening of medications against a selective protein molecule or biomarker is performed (vHTS). Most biological targets reflect disease processes or systems; therefore, this method is more successful than drug-oriented strategies. Disease model information requires disaster response to focus on illness/therapy.⁴⁸ DR may be caused by illness and medication, according to proteomics, genomics, metabolomics, and phenotypic data (off-target mechanism, pharmacological targets, disease trails, pathological circumstances, contrary and adjacent effects, etc.).⁴⁹ Cells and metabolism incorporate disease-specific networks, genes, markers, and chemicals. Figure 4 depicts the drug transport. Over half of FDA-approved small molecule drugs and biologics are phenotypic or target-based. Chance-based methods can screen small-molecule libraries. Target-based techniques choose medications based on therapy goals. Like disease-based repositioning, treatment/therapy-based repositioning relocates products⁵⁰⁻⁵²—Table 2 displays drug operations.

Figure 4.

Diagrammatic illustration of methodologies and procedures for repositioning a medication.

3.1. Target-Based Techniques

High-throughput screening (HTS) and high-content screening (HCS) of therapeutic medicines may be conducted in vitro and in vivo to specifically target crucial protein targets or biomarkers. Additionally, in silico screening of chemicals or drugs can be performed using a vast chemical reference library, such as ligand-based screening or molecular screening dockage. Blinded search techniques have a lower chance of finding potential medicines or treatments. Screening is faster. A biological target tests a drug candidate’s biological reaction (such as a protein or a receptor). Using a drug’s protein targets, this method identifies new indications. Using primary and off-target proteins, a drug’s indication can be changed. “Target repositioning” is when a novel sign is combined with an existing protein target; 80% of pharmacological repositioning studies use this method.⁵⁷ When a previously approved drug interacts with a tributary target, this is called “off-target repositioning”.

3.2. Knowledge-Based Strategies

Bioinformatics or cheminformatics techniques can collect information on drug profiles, drug–target networks, biochemical structures, and clinical trial data such as adverse events, signaling, and metabolic pathways. Blindfolded or target-based strategies have less information.⁵⁸ Current data can predict unknown novel processes like therapeutic targets, drug–drug resemblances, new disease biomarkers, etc.⁵⁹

3.3. Signature-Based Techniques

Disease omics statistics (genomic evidence) can be used with or without medication to find off-target and illness-causing chemicals. Signature-based medication repurposing relies on gene profiles derived from illness omics data collected with or without therapy. Next-generation sequencing and microarray technology generate massive amounts of genomics data for medication repurposing research.⁶⁰ Using this information, disease-modifying gene signatures can be created. NCBI GEO, SRA, CMAP Connectivity Map, and CCLE Cancer Cell Line Encyclopedia contain genomics-related information. For the repurposing of drugs, a computer-accessible library of gene signatures is needed. Using molecular mechanical details, such as altered gene expression and protein appearance changes, in signature-based approaches such as WGCNA, CMap, and the Collection of Integrated Network-Based Cellular Signatures can reveal previously unknown drug action mechanisms (LINCS).^61,62 These approaches can investigate the mechanisms of the medication action. This investigation employs computational methods to investigate molecular pharmacological processes, such as changes in gene expression, with Figure 5 illustrating the different computational methodologies for drug repositioning.^63,64

Figure 5.

Diagram depicting the numerous computational approaches to medicine repurposing using databases, artificial intelligence, visual learning, and Insilco for analyzing and comprehending the treatment of diverse ailments. The provided graphic depicts a visual depiction of several computational methodologies used in the process of drug repurposing. These novel approaches use a range of tools and technology, including databases, artificial intelligence, machine learning, and in silico modeling, to examine and understand the possible therapeutic uses for a wide array of medical ailments. This diagram serves as a succinct visual aid, emphasizing the dynamic nature of drug discovery and the significant contribution of computational tools to the identification and advancement of repurposed medications. This statement highlights the increasing significance of data-driven and technology-driven approaches in the progression of healthcare research and therapies.

3.4. Pathway/Network-Based Approaches

Disease-specific omics data, pre-existing signaling or metabolic pathways, and protein interaction networks can be used to build disease-specific circuits for pharmaceutical repositioning. These strategies may reduce the number of proteins in general signaling networks (or target molecules). Trail or network-based techniques benefit from illness omics data such as drug–target interactions and treatment mechanisms. So, an extensive network with many paths can have a few specified destinations. A pharmaceutical repurposing study revealed metastatic breast cancer subtypes.^65,66

3.5. Targeted-Mechanism-Based Strategies

Combining omics data, signaling circuit information, and protein interaction networks reveals drug action mechanisms. These methods identify the processes associated with using medications to treat specific issues and the agents linked to diseases or pharmaceuticals. Target-based screening involves testing a drug candidate against a single biological target (such as a protein or receptor). By establishing a link between a medication’s protein targets and a specific condition, this technique enables the discovery of potential new indications for therapy. As stated, it is possible to choose a further sign for a given pharmaceutical by considering the prime target protein and any off-target proteins that the drug interacts with. “Target repositioning” interacts with a known target protein to provide a new indication. 80% of pharmaceutical repositioning projects use this method. Off-target repositioning uses an approved medicine and a secondary target to treat a unique sign.^50,54,67Figure 6 depicts the different repositioning techniques and Table 3 portrays the numerous classes of medications undergoing establishment for repositioning and pharmaceuticals that have already been developed under the drug repositioning approach, respectively.

Figure 6.

Repositioning strategies using drawings. HTS/HCS refers to high-throughput and high-content screening. Stratagem 1 (S1): accidental remark. Stratagem 2 (S2): evaluating unique activities (particular illness phenotype, reasoned approach). S3: a unique drug–target interaction. Fourième stratagem (S4): novel protein functions for recognized targets. Stratagem 5 (S5): biochemical processes. Stratagem 6 (S6): disease-specific repositioning. Stratagem 7 (S7): unanticipated harmful properties.

Table 3. Some Illustrations of Medications That Have Been Repositioned after First Being Approved or Investigated.

The Pharmacological Classification of the Medication	Inventive Sign	Novel Sign	Developmental Status
Duloxetine, selective serotonin reuptake inhibitors	Clinical depression	Generalized anxiety disorder, fibromyalgia syndrome, and nerve pain are included in this list.	So far establisheda
Everolimus	Anti-rejection drugs	Islet cell tumor	So far establisheda
Favipiravir	Flu	Covid-19	Ongoinga
Fluorouracil, antimetabolite	Carcinoma	Angiosarcoma	So far establisheda
Fluoxetine	Depression	Premenstrual dysphoric disorder (PMDD)	So far establisheda
Gabapentin	Epilepsy	Dysesthesia	So far establisheda
Galantamine	Neuromuscular paralysis	Alzheimer-type dementia (ATD)	So far establisheda
Hydroxychloroquine	Malaria, RA	Covid-19	Ongoinga
Ibudilast	Bronchial asthma	Dysesthesia	So far establisheda
Imatinib	CML, ALL	Gastrointestinal stromal tumor	So far establisheda
Isoniazid	TB	A few forms of tumors	So far establisheda
Itraconazole	Mycosis	Malignance similar to NSCLC	Ongoinga
Ivermectin	Scabies, River blindness, helminthiases	Covid-19	Ongoinga
Ritonavir/lopinavir	HIV/AIDS	Covid-19	Ongoinga
Metformin	DM (type 2)	Breast and colon carcinoma, CVDs	Ongoinga
Methotrexate	Carcinoma	Psoriasis, RA	So far establisheda
Milnacipram	Depression	Fibromyalgia	So far establisheda
Miltefosine	Carcinoma	Kala-azar, amoebiasis	So far establisheda
Mifepristone	Misoprostol combined with pregnancy termination	Hypercortisolism	So far establisheda
Minoxidil	High blood pressure	Male-pattern baldness	So far establisheda
Nelfinavir	HIV/AIDS	Ductal carcinoma, non-small-cell lung cancer (under clinical trials)	Ongoinga
Nitroxoline	Urinary tract infection	Breast, bladder, and pancreatic carcinoma	Ongoinga
Orlistat	Adiposity-based chronic disease	Carcinoma	So far establisheda
Pimozide/penfluridol	Mental health disorders	Ductal carcinoma	Ongoinga
Propranolol	High blood pressure	Classic migraine	So far establisheda
Remdesivir	Ebola virus disease (EVD) (failed in a clinical trial)	Covid-19	Ongoinga
Retinoic acid	Acne	Severe lymphoblastic leukemia	So far establisheda
Ribavirin	Viral illnesses like RSV and hepatitis C	Blood carcinoma (RBCs and WBCs)	Ongoinga
Ropinirole	PD	Willis–Ekbom disease	So far establisheda
Sildenafil	Angina pectoris, pulmonary arterial high blood pressure	Impotence	So far establisheda
Simvastatin	Cardiovascular disorders	Bronchogenic carcinoma	So far establisheda
Sunitinib	RCC, imatinib-resistant GIST	Islet cell cancers	So far establisheda
Tamoxifen	Ductal carcinoma	Disseminated lupus erythematosus	So far establisheda
		NTDs like leishmaniasis	Ongoinga
Thalidomide	Immunomodulation, hyperemesis gravidarum (withdrawn)	Multiple myeloma, Hansen’s disease	Previously establishedb
Tocilizumab	RA	Covid-19	Ongoinga
Topiramate	Fungal infection	IBD	So far establisheda
Valproic acid	Epilepsy	Manic depression bipolar disorder, migraine headache	So far establisheda
Valsartan	Hypertension, heart attack	AD	So far establisheda
Zidovudine	Carcinoma (failed clinical trial)	HIV/AIDS	Previously establishedb
Amphotericin B (AMB)	Mycosis	Kala-azar	So far establisheda
Aspirin	Pain and inflammation	Cardiovascular disorders	So far establisheda
		Adenocarcinoma	Ongoinga
Amantadine	Flu	PD	So far establisheda
Astemizole	Hives	Malaria	Ongoinga
Atomoxetine	Clinical depression	Disorders of inattention and hyperactivity	So far establisheda
Avermectin	Onchocerciasis, lymphatic filariasis	TB	Ongoinga
Azithromycin	Microbial contaminations	Covid-19	Ongoinga
Bromocriptine	PD	DM (type 2)	Ongoinga
Bupropion	Clinical depression	Smoking termination	So far establisheda
Celecoxib	Tenderness	Chest and colorectal carcinoma	Ongoinga
Chloroquine	Malaria	Covid-19	Ongoinga
Cimetidine	Pectic ulcer	Chest, lung, and prostate carcinoma	Ongoinga
Crizotinib	Non-Hodgkin’s lymphoma	Non-small-cell lung cancer	Previously establishedb
Colchicine	Primary gout or secondary gout	Idiopathic pericarditis	So far establisheda
		Covid-19	Ongoinga
Daunorubicin		Angiosarcoma	So far establisheda
Digoxin	Cardiovascular disorders	Adenocarcinoma of the prostate	Ongoinga
Dimethyl fumarate	Psoriasis	Encephalomyelitis disseminates	So far establisheda
Disulfiram	Enduring alcoholism	Carcinoma	Ongoinga

^aReferences (39, 54, and 68−72). Indicates successful repurposing of FDA-approved drugs.

^bIndicates successful repositioning from investigational new drugs (IND).

The utilization of visual representations in the form of drawings effectively clarifies seven distinct tactics utilized in the endeavor of repurposing medications. The stratagems discussed in this context encompass a wide range of approaches including both accidental discoveries and meticulously reasoned evaluations. These approaches encompass various techniques such as high-throughput and high-content screening (HTS/HCS), exploration of unique disease phenotypes, investigation of novel drug–target interactions, exploration of expanded protein functions, examination of biochemical processes, investigation of disease-specific repositioning, and consideration of unanticipated adverse properties. This graphic depiction serves as a complete resource, elucidating the many innovative approaches used in the effort to repurpose drugs for a broad spectrum of therapeutic uses. The statement highlights the intricate nature and creative problem-solving inherent in the discipline of medication repositioning, which is always evolving to tackle healthcare obstacles and investigate new therapeutic opportunities.

4. Experimental Approaches

Proteomic methods, such as affinity chromatography and mass spectrometry, have uncovered more drug-binding partners. Repurposing, drug targeting, off-target research, and studies are all partners in the current era of chemical biology in target validation. CETA predicts the heat stability of target proteins using drug-like ligands with cellular empathy.⁷³ For this, CETA was used. Protein kinase drug discovery requires addressing the promiscuity of protein kinase inhibitors and developing improved preclinical probe chemicals, which may influence clinical medication progress and repurposing. Parameters must be met because of protein kinase inhibitor promiscuity.⁷⁴ Early, unbiased affinity techniques are effective for assessing the drug effects on cells. Inhibitor-induced paradoxical kinase activation causes off-target tumors in patients. Chemical genetics may help us understand biological system binding and performance. These findings may be rapidly applied to other therapeutic areas or exploited to minimize drug-resistance implications of extended revelation, which are phenotypic responses to kinase-inhibitor-based cancer therapy. Figure 7 compares the computational technique to experimental ways of achieving drug repositioning objectives. Sorafenib and dasatinib may affect (or invalidate) the treatment of specific patient groups.⁷⁵⁻⁷⁸

Figure 7.

Illustration depicting computational techniques and experimental approaches. The provided picture effectively depicts the mutually beneficial interaction that exists between computational tools and experimental procedures within the field of scientific inquiry. The graphic representation illustrates the amalgamation of state-of-the-art computational tools and conventional experimental procedures, demonstrating the collaborative nature of these two components in the pursuit of knowledge and the promotion of innovation. The provided graphic depiction serves as a visual reminder of the multidisciplinary nature inherent in contemporary research. It effectively showcases the interconnectedness and collaboration among computer modeling, data analysis, and experimental practices, which together contribute to the generation of novel insights and problem-solving approaches across many scientific fields. This statement emphasizes the significance of adopting a comprehensive methodology that combines computational and experimental techniques in order to address intricate scientific problems.

5. Obstacles to Medication Reformulation

When discussing repurposing medications, it was said that this technique has already attained a high degree of success. However, there is no guarantee that the new application will succeed. Prior attempts to use these pharmacological choices in a new context have failed, with the majority occurring in phase III clinical trials.⁷⁹ As with the expansion of novel medications, toxicity is anticipated in late-stage drug development; however, since the safety profiles of candidates have already been established, these failures have a lower chance of being linked to toxicity.^80,81 However, in the last stages of development, setbacks are to be anticipated. No matter how hard you try, it is not uncommon for late-stage development initiatives to fail. Other factors contribute to repurposing failures, such as the inability to go further with a promising candidate in the early stages of the process. These difficulties include difficulty with patents and legislation and organizational obstacles. Accordingly, the unsuccessful repurposing medication candidates are included in Table 4.

Table 4. Repurposed Failed Drug Candidate (Few Selected Examples)^a.

Drug Name	First Indication	Novel Indication	Date	Utilized a Repurposing Strategy	Consequence of Repurposing
Latrepirdine	Antihistamine	Huntington disease	2011	Pharmacological analysis	The Phase 3 HORIZON dimebon (latrepirdine*) experiment in Huntington disease patients did not show statistical significance for cognitive or global function, according to Pfizer and Medivation. Highly unmet need ended the study.
Ceftriaxone	Antibiotic	Amyotrophic lateral sclerosis	2014	In vivo high-throughput drug testing	The Phase III study had ineffective results.
Topiramate	Epilepsy	Inflammatory bowel disease	2014	Transcriptome-based signature matching	Ineffective in a retrospective cohort study yet beneficial in a rat model of inflammatory bowel disease; no randomized clinical trial has been conducted to date.

^aEven though screening efforts are comparatively cheap, directing clinical trials of permitted drugs is not. A druggist and blogger describe the advantage of medication repurposing is that inventors have already accomplished the early stages of clinical growth so that the drugs can go directly to humanoid studies.

6. Industry-Wide Organizational Obstacles

As a result of the realization that there is potential in repurposing drugs for use in illness areas outside of their core emphasis, pharmaceutical corporations are forming relationships with smaller biotech groups and academic institutions. Repurposing may provide organizational issues in the pharmaceutical industry, especially if the repurposed sign does not belong inside the primary illness category of the company. Repurposing may also be hampered by regulatory obstacles.¹ One viable answer to this problem is utilizing external resources for pharmaceutical distribution, such as contract manufacturing companies, regulatory assistance, and pharmacovigilance.⁸²

7. Network-Based Stage-Specific Drug Delivery

Using a network-based approach, Kyriaki et al. reused pharmaceuticals. Repurposed medications were evaluated using a network-based result that is preferable to unsuccessful, permitted, or active therapies. Reclassification of drugs may occur in accordance with criteria pertaining to their structure, function, or prior knowledge. Evaluation of the blood−brain barrier’s (BBB) permeability is a component of the reclassification process. Due to commonalities, they propose repurposing ten drugs for each of the three stages of Alzheimer’s disease. They prioritize AD validation research using a network-based method. Using transcriptome data sets, we classified AD gene signatures using network-based, CoDReS, and BBB permeability classifications.⁸³⁻⁸⁵ 26 drugs were repurposed across three severity categories. The computational and literature-based analysis found 95 similar pathways, including pharmacological targets and AD-related genes in DisGeNET.⁸⁶ Most highlighted drugs are structurally different, indicating different classes. 2016 computer simulations identified saracatinib; 2017 clinical trials began. This study evaluates the impact of pharmacological repurposing on AD staging using a network-based approach.⁸⁷ In 2014–2019, saracatinib was studied for mild Alzheimer’s; after 52 weeks, researchers tested glucose metabolism, cognition, and brain growth. Entorhinal and hippocampus decreased less with saracatinib than with placebo; 2016 data show pioglitazone’s promise. Pioglitazone was withdrawn in 2018 because it did not delay MCI. Insufficient BBB permeability and side effects hindered diabetic therapy trials. They rethought this drug; Jojo et al. made pioglitazone nanocarriers.⁸⁸ Identifying this medicine using 2016 and 2020 data and researchers’ attempts to optimize its use for AD may mean the medication is still possible with future changes and optimization. Alzheimer’s is sometimes inherited, and sometimes it is not inherited. Pathways like Ca2+ signaling, cholinergic, GABAergic, and gap junction are repeated; these pathways cause the disease, and MAPK signaling deficiencies cause Alzheimer’s disease.⁸⁹⁻⁹² AD genes are similar to those of ACE, ESR1, and CYP2D6. DisGeNET ranked ACE second for the disease. Renin-angiotensin regulates the blood pressure of ACE1. ACE and AD are mechanically related. Blocking ACE1 in the rat hippocampus enhances memory and lessens the likelihood of developing Alzheimer’s disease. ACE inhibitors reduce blood pressure, decreasing the risk of Alzheimer’s disease (AD). The drugs are ineffective against the protein associated with Alzheimer’s disease, as well as certain variations in the estrogen receptor alpha gene known as ESR1I SNPs.⁹³ Two types of estrogen receptor 1 (ESR1) were linked to Alzheimer’s disease in Asian people but not in Europeans, according to a study that looked at 8,288 cases and controls. Some types of ESR1 may help protect the brain from AD by stopping the harmful effects of amyloid-β protein, which hurts brain cells. Alzheimer’s disease ruins memory, the ability to think clearly, and the ability to do things. Symptoms show up later in life.⁹⁴ Studies show that gene mutations affect drug metabolism and safety, e.g., donepezil’s CYP.⁹⁵ The pharmacokinetics and effectiveness of donepezil may be influenced by gene polymorphisms in the CYP2D6 gene. Clomiphene acts as both an estrogen agonist and antagonist via its targeting of ESR1. The drug iloperidone, which is used to treat Alzheimer’s, blocks D2 and 5-HT2A receptors in the brain. People with Alzheimer’s disease may benefit from medicines, which offer unmatched safety and efficiency. Depression is a common symptom of Alzheimer’s disease, similar to other kinds of dementia.⁹⁶⁻⁹⁸ Unconventional use of the antidepressant paroxetine has been shown to be effective in treating both depression and Alzheimer’s disease. In the study of Alzheimer’s, monoclonal antibodies are used. Amyloid beta is a treatment for AD approved by the FDA (Ab). Scientists rely on molecules. The DNA of those with Alzheimer’s disease is utilized. Alzheimer’s disease is only one example of a brain condition.⁹⁹ Reasons: hypoxia neurodegenerative brain tissue often lacks premortem data. The research suggests network-based strategies for pharmaceutical repurposing. Alzheimer’s drugs were found using a network-based computational method based on disease-related genes, pharmacological targets, and drug-candidate gene expression patterns. Our network rates reused drugs. Functional connotation, structural variety, blood–brain barrier penetrability, and overall similarities are used to select Alzheimer’s medications. This method studies addiction stages and the use of repurposed drugs. They used a network-based method to screen for repurposed drugs. We found the best repurposed Alzheimer’s drugs using this strategy. Using 2016 data, we linked the therapeutic targets of our top repurposed pharmaceuticals to Alzheimer’s. In vivo and clinical drug testing is growing. Alzheimer’s drug targets are found using DisGeNET data. Our repurposed drugs may help AD research.^100−105

8. Using Well-Known Disease–Drug Combinations and Cutting-Edge Computational Drug Repurposing Techniques: A Novel Approach

The authors propose ML-based drug repurposing—antidrug research. Our third data source is human illness, cell line gene expression patterns, and FDA-approved medications and disorders: FDA-approved drugs and supervised machine learning.

Nafisih repurposed drugs with AI. Clinical data and disease- and medication-related gene expression patterns are combined. Their study uses DML because FDA-approved drugs are closer. Both malignancies are described.¹⁰⁶ A comparison was made between primary invasive tumors and normal stroma, with a sample size of 6. The identifier for the data set is GSE26910.¹⁰⁷ Four samples of ductal carcinoma and two samples of normal tissue were evaluated using the Affymetrix U133A platform, as described in the study by Pau Ni et al. (2010).¹⁰⁸ The Cancer Genome Atlas Research Network conducted RNA-seq analysis in 2012.¹⁰⁹ In 2012, the National Cancer Institute and the National Human Genome Research Institute started the Cancer Genome Atlas (TCGA) Research Network.^109,110 This is a program that looks for similarities, differences, and new themes in different types of cancer and organs. The project looked at more than 30 individual cancers and made more than 2.5 petabytes of data. The data set has TCGA-3, GSE26910, and GSE1299 in it. Ambroxol, ciclopirox, and daunorubicin were investigated. Daunorubicin is an effective medication for treating ductal cancer. Anthracyclines exert inhibitory effects on topoisomerase II (TOPII) and are effective against lobular carcinoma.¹¹¹ Daunorubicin is a very effective medicine for the treatment of ductal carcinoma. Anthracyclines have inhibitory effects on topoisomerase II (TOPII) and are effective against lobular cancer.¹¹¹ Therefore, daunorubicin is a medication that specifically targets TopoII-alpha. Phase I clinical trials investigated the use of daunorubicin in the treatment of breast cancer (ClinicalTrials.gov identifier: NCT00004207).^112,113 Ambroxol is a pharmaceutical substance. The enzyme CYP3A4 inhibits the growth of breast cancer. Ambroxol is a substance used in medicine. Repositioning antifungals containing cyclophorox, which inhibits the proliferation of breast-cancer-causing enzyme CYP3A4, can prevent cancer. Cyclophorox antifungals can prevent cancer.¹¹⁴

IPF-affected pulmonary explants were analyzed with U133 Plus 2.0 arrays.¹⁰⁶ 40 IPF and eight healthy people are compared in GSE5312F (2015). 93 IPF and 30 healthy samples were microarray-analyzed. Data from Lung Genomics Consortium: 61 ILD, 17 controls (GEO ID: GSE47460). Supplements treat IPF. Low-IPF NSCLC is treated with erlotinib/gefitinib. Anti-EGFR medications reduce lung fibrosis.¹¹⁵ Gefitinib and erlotinib inhibit bleomycin-induced fibrosis (2008). EGFR inhibitors may treat IPF. Sorafenib heals RCC.

RA maintains and manages two databases. Gene expression in healthy synovial tissue (n = 5) is compared to gene expression in individuals with rheumatoid arthritis (RA). RA is responsible for the maintenance and management of two databases. The gene expression in healthy synovial tissue (n = 5) is being compared to the gene expression in patients diagnosed with rheumatoid arthritis (RA). This study aims to investigate the biological repercussions in the year 2010. Microarrays are used to compare 18 samples from individuals with rheumatoid arthritis (RA) and 15 samples from healthy individuals. The identifier for the data set is GSE15573. The geospatial data set RA has a list of treatments, which may be found in ref (116). The study emphasized a number of recently identified genes that have the potential to contribute to the identification of innovative clinical biomarkers utilized in diagnostic, therapeutic, and treatment processes. Sirolimus alleviates rheumatoid arthritis. Soil includes the compound sirolimus, also known as rapamycin. The study investigates the relationship between sirolimus and RA/autoimmune cytopenias, with the ClinicalTrials.gov number being NCT00392951. Trimipramine and verteporfin are being investigated for their potential in treating the pain associated with rheumatoid arthritis using a novel computational drug repurposing approach that leverages existing knowledge of disease−drug pairs. The discomfort caused by rheumatoid arthritis was alleviated.¹¹⁷

Electronics recycle drugs. We offer a machine-learning-based technique for repurposing medicines. We classify disease-fighting medications using supervised machine learning. 20,000 genes from 9 data sets and 500 CMap and LINC examples were analyzed. This helps us evaluate drugs. We found medicines to test whether DML causes LLE performance (competing methods 3 and 4). LLE-DML is lost to diminution. Some prefer LLE and DML. Reporting pharmacological chemistry, biomarkers, target pathways, and symptomatology may help. Innovative repurposing includes network-based and disease–drug-paired computing.

Kyriaki et al. and colleagues recycled 26 drugs; most highlighted medications are structurally diverse, suggesting different classifications. Science is necessary to understand Alzheimer’s. Alzheimer’s is treated with antipsychotics. Estrogen is suppressed by clomiphene; the choice of an Alzheimer’s drug is influenced by its function, structural diversity, BBB permeability, and similarity. The method determines the phases of Alzheimer’s and potential therapies. Drug target pathways resemble AD pathways according to DisGeNET. Their medication schedules are automated. Novel applications include computer-aided medication repositioning. They were combining data related to health. ML compares and ranks pharmaceuticals. The 20,000 genomes and 500 tablets were obtained from the CMap Improved and LINCS medication rankings, respectively. DML or dimensionality reduction might enhance LLE-DML (an LLE-DML failure). LLE and DML (LLE) are drug-related illness clusters.^101,103

9. Regulatory Considerations and Intellectual Priorities

The generality of repurposing cases is permitted preceding the termination of the original product patent in the US (69.6%) and the EU (83.3%). Article 8(3) (complete dossier) submissions qualify for ten years of data exclusivity for repurposed medications that are not orphan pharmaceuticals. Claims for novel signs of deep-rooted medicines presented following Article 10.5 may be given one year of information individuality. Existing marketing authorization is free from data exclusivity regulations. Traditional drug development methods are costly, dangerous, and riddled with failure.^118,119 In recent years, identifying innovative therapeutic uses for existing medications has garnered increased focus on drug repositioning. Regulatory standards may need further preclinical and clinical investigations if the data presented are inadequate. Patent applications and intellectual property rights also rank among the most significant issues (IPR). According to intellectual property and patent regulations, there are no IP protection alternatives for medication development employing repositioning techniques.^120−124

Box 2. Glossary 2.

European Union and United States Regulatory Procedures for Repurposed Pharmaceuticals

• Directive 2001/83/EC (predominantly provisions 6, 8, 3, and 10(3) and (5)) serves as the primary legal foundation for drug applications for repurposed pharmaceuticals. There are three methods to apply for repurposed medications in Europe: centralized and decentralized.

  National or decentralized (mutual recognition).

• Information on pharmaceuticals (physicochemical, etc.). It should be included in the application.

  Nonclinical tests (biologic or microbiological) (toxicological and pharmacological). Clinical trials and bibliographic records can fulfill some data needs.

  Data. In addition, for applications based on data from a reference, see article 10 (abridged).

  Data requirements for a pharmaceutical product could be decreased.

• Prior clinical experience (such as trial results) may help determine safety.

  Data or data gathered after a campaign has ended.

• A risk management plan should be included with all applications.

• A risk management plan should be attached to every application.

• Before applying article 8(3), the European Medicines Agency (EMA) must agree on a Paediatric Investigation Plan or waiver.

• A variant application could be used to add a new indication for an approved medicine.

United States

• Section 505(b)(1), section 505(b)(2), or section 505(b)(3) may be followed when submitting a drug application for repurposed pharmaceuticals (j).

• To make minor adjustments (label, novel dosage or strength, etc.), a manufacturer must file a supplementary NDA for a product with an already-approved new drug application (NDA or biologics licensing claim (BLA) for biologic medicines).

Table 5. Statutes in Crucial Markets That Provide Economic Incentives for Orphan Medicine Research^a.

Parameter	USA	Japan	Australia	EU
Authorized outline	Orphan Medication Act (1983)	Orphan Medication Guidelines (1993)	Orphan Medication Policy (1998)	Guideline (CE) N°141/2000 (2000)
Involve governmental agencies	FDA/OOPD	MHLW/OPSR (Orphan medication division)	TAG	EMEA/COMP
The disease’s incidence (per 10,000 persons) supports its orphan designation.	7.5	4	1.1	5
Prevalence and impacted population size estimation (per 10,000 individuals)	20 million	No information	No information	No information
Credit for taxes	Yes, 50% for clinical research	Yes, 6% of any research is restricted to 10% of the business.	No	Governed by the member countries
Funding for examination and investigation	Agendas of the National Institutes of Health and others	Governmental funds	No	FP6 managed by the member states + national measures
Reconsideration of requests aimed at orphan designation	No	Yes	Yes (every 12 months)	Yes (every six years)
Help with the preparation of the application dossier	Yes	Yes	Yes	No
Augmented advertising process	Yes	Yes	Yes	Yes (through the centralized process)

^aGiven the limited scope of patent protection for repurposed generic products—often limited to the underlying “method of use”—regulatory protection in rare illnesses is crucial. This means that many resources are being redeployed here. Two hundred and thirty-six medications with promising results against rare diseases but no commercial approval were found by comparing the FDA approvals database with those pharmaceuticals that have acquired orphan drug classification.¹⁴

10. Patent Contemplations

Drug repurposing faces a variety of roadblocks, including intellectual property laws and regulations.¹⁻⁴ Due to intellectual property laws and other restrictions, it is challenging to reuse medications.¹ Most significant pharmaceutical markets will protect an innovative and creative (i.e., not evident) new medical application of a well-known medicinal chemical (that is, nonobvious). It is still possible to find many applications for repurposing via either published scientific research or clinical practice. Even if clinical trials have not shown¹²⁵ their efficacy, this may make it more difficult for them to get patent protection. While it may be challenging to prove that a generic manufacturer has violated the new MOU patent by labeling its product solely for nonpatented indications (also known as “skinny labeling”), generic manufacturers that do not promote the use in the patented expression by any other means will have a difficult time proving patent infringement claims against them.¹²⁶ One obstacle is the lack of medications that can be reused. The United Kingdom’s House of Parliament presented the Off-Patent Drugs Bill 2015–16 in June 2015.¹²⁷ This rule aimed to control the unapproved use of medicine whose patent had long since expired. Despite the backing of health organizations, the UK Parliament voted against it. The Association of Medical Research Charities (AMRC) researched pharmaceutical repurposing in the United Kingdom in November 2017. NICE, MHRA, the Royal Colleges, and industry representatives contributed to this report’s development.^128,129

Incentives for generic pharmaceutical companies to pursue medication repurposing and a system for keeping tabs on the drug repurposing framework are both called for in this article. In the United States, the patent term of a commercial pharmaceutical that has the potential to treat rare diseases is extended by six months thanks to the OPEN ACT (Orphan Product Extensions Now Accelerating Cures and Treatments).¹³⁰ Additional methods of increasing patentability include the creation of new formulations, dosage forms, or chemicals with a comparable therapeutic effect and acquisition of exclusive marketing authorization in new regions. In other cases, commercially available generic versions may not be able to meet the needs of a newly repurposed usage, which involves a customized formulation and dosing regimen.¹

11. Recommendations for Future Prospective and the Repurposing of Medications

There is a long history of therapeutic compounds being found via repurposing pharmaceuticals, primarily by accident and serendipity. Recently, it has enabled the development of novel medicines based on already-approved pharmaceuticals. Strategic repositioning of medications has benefitted from a more scientific and rigorous approach, which has led to the identification of therapeutic signals in pharmacological compounds that were previously unknown. The popularity of medication repositioning is growing due to cheaper research costs, improved possibility of achievement, less examination time, and reduced asset risk. Consequently, these benefits have enabled the concentration of drug research programs for almost all human disorders. Utilizing in silico approaches such as SBDD and pharmacophore modeling tools, as well as AI technologies, may help expedite the repurposing of drugs. In the era of precision medicine, researchers have investigated novel bug/metabolic/gesturing approaches, off-target effects, and target-specific mechanisms/gene expression patterns to enhance the efficacy of pharmaceutical repositioning. Numerous factors, including next-generation sequencing, microarray data, and transcriptomics, have significantly increased the number of genomic and transcriptome data. Utilizing network and systems biology and understanding the molecular and genetic levels may help reveal new action mechanisms. Pharmaceutical repositioning strategies must include computational and experimental procedures to achieve high success rates for relocated pharmaceuticals. Pharmacological repurposing may be an effective technique for developing novel medications to treat human ailments.

According to an assessment of the advantages and disadvantages of pharmacological repurposing, we provide six suggestions for enhancing this strategy. Initially, improved data analytics tools are necessary. Using big data to uncover chances for repurposing offers several benefits. Despite this, there remain considerable impediments to clinical data integration and accessibility (including clinician notes in patient case records). Future research must be adaptable and evaluable by a more comprehensive number of “nonexperts”, necessitating the development of creative technical explanations that decrease the necessity for human curation and enable the integration of many kinds of omics data. Second, pharmaceutical companies must make their preclinical and clinical drugs available to the general population. The Medical Research Council (MRC) and the National Institutes of Health’s Center for Advancing Translational Sciences (NCATS) are doing good work. Still, university researchers need access to more molecules, preferably in vast libraries. Compound delivery and material transfer agreement signatories are two procedures that might be simplified in the future. In Phases II and III, industry-funded research should be more accessible. Researchers from other universities can evaluate the data and identify previously undiscovered tendencies, which may lead to new opportunities for repurposing current efforts. Repurposed medications may bring additional risks to patient safety, which must be considered. Awareness of the increased risks associated with repurposed drugs is essential. Because the medication is being administered to new populations or its dosage schedule has been adjusted, these interactions may be the outcome of these factors (e.g., chronic rather than intermittent dosing). Repurposing programs need increased funding for appropriate technologies, compound availability, and the growth of the interchange of drug-repurposing library collections. People with uncommon diseases need new funding sources for pharmaceutical repurposing techniques. Patent and regulatory impediments must be eliminated before pharmaceutical repurposing. Repurposed indications may benefit from longer data exclusivity periods, royalty agreements with generic companies, or other legislative enhancements that increase the likelihood of investment recovery in repurposing programs.

Glossary

Abbreviations

NMEs

New molecular entities

ENL

Erythema nodosum leprosum

FDA

Food and Drug Administration

MOU

Memorandum of understanding

IPR

Intellectual property rights

HCS

High content screening

HTS

High throughput screening

vHTS

Virtual high throughput screening

DR

Drug repurposing

NCBI GEO

National Center for Biotechnology Information Gene Expression Omnibus

SRA

Steroid receptor RNA activator

CMAP

Connectivity map

CCLE

Cancer Cell Line Encylopedia

WGCNA

Weighted gene co-expression network analysis

LINCS

The Library of Integrated Network-based Cellular Signatures

SCPMF

Similarity constrained probabilistic matrix factorization

GWAS

Genome-wide association studies

DMOG

Dimethyl oxalylglycine

CETA

Comprehensive Economic and Trade Agreement

EHRs

Electronic health records

LLE

Nonlinear dimensionality reduction algorithm

DML

Dimensionality reduction machine learning

SBDD

Structure-based drug design

Author Contributions

The study’s conception and drafting were carried out by M.V., whereas the methodologies and manuscript were developed by A.S.M. Supervisory and editing duties were carried out by S.P.M.

The authors declare no competing financial interest.