Filling data gap for nicotinic acid, nicotinate esters and nicotinamide for the determination of permitted daily exposure by a category approach

Abstract

This study aimed to obtain necessary toxicological data using experimental and computational methods for the calculation of a common permitted daily exposure (PDE) which can be relevant for nicotinic acid and its esters and nicotinamide according to European Medicines Agency Guideline on setting health-based exposure limits. PDE calculation is mainly based on critical toxicological endpoints. During this procedure, critical toxicological endpoints data of an active pharmaceutical ingredient (API) may not be able to find satisfactorily. Hence, using toxicological data for another API that has a similar chemical structure can be a useful way. In this study, toxicological endpoints of nicotinic acid and its esters and nicotinamide were evaluated. Then, the data gaps in the toxicological endpoints were filledusing the read-across approach. Based on the current existing data, nicotinic acid and its esters and also nicotinamide are not genotoxic and do not have skin sensitization potential. These compounds do not present a concern for carcinogenicity and developmental/reproductive toxicity. Based on these critical endpoints and available experimental data, the final PDE of 10 mg/day was calculated for all category members. Our study showed the utility of the read-across for PDE calculation of APIs with experimental toxicological data gap.

Electronic supplementary material

The online version of this article (10.1007/s43188-020-00069-8) contains supplementary material, which is available to authorized users.

Introduction

Niacin, also known as nicotinic acid and vitamin B3, is a water-soluble vitamin belonging to the vitamin B family, which occurs in many animal and plant tissues, mainly as the nicotinamide nucleotides. Niacin is converted to its active form niacinamide, which is a component of the coenzymes nicotinamide adenine dinucleotide (NAD) and its phosphate form, NADP. These coenzymes play a vital role in tissue respiration and in glycogen, lipid, amino acid, protein, and purine metabolism [1].

Over the past forty years, nicotinic acid and its esters (methyl, ethyl and benzyl nicotinate) have become a proper candidate for various therapeutic applications. Nicotinate esters act as a prodrug, which cross the skin rapidly and release nicotinic acid. They provoke vasodilatation and increase cutaneous blood flow, at least partly by forming vasodilating prostaglandins [2]. These esters of nicotinic acid are used as an active ingredient as a rubefacient in over-the-counter topical preparations to relieve pain in muscles, joints and tendons, and other musculoskeletal pains in the extremities [3]. Causing the blood vessels of the skin to dilate, which gives a soothing feeling of warmth and the irritation of the sensory nerve endings, are the possible mechanisms of their analgesic effect [4].

A recently introduced EU GMP Guideline for Medicinal Products for Human and Veterinary Use ANNEX 15 [5] explains the principles of qualification and validation applicable to the facilities, equipment, utilities, and processes used for the manufacturing of medicinal products. Accordingly, limits for the carry-over of product residues should be determined by permitted daily exposure (PDE) calculation for active pharmaceutical ingredients (API) based on critical toxicological endpoints, such as repeated dose toxicity, genotoxicity, carcinogenicity, developmental/reproductive toxicity, and hypersensitivity potential. We should note here that this PDE evaluation is not a reevaluation of registered drugs for their safety. The main aim of the European Medicine Agency (EMA) guideline [6] is to obtain a PDE limit for API, which will be used in the cleaning validation process of production equipment in pharmaceutical companies. The PDE represents a daily dose that is likely to be without a perceptible risk of deleterious effects to the potential patient population during an average lifetime [7]. For PDE determination, critical toxicological endpoints of an API are searched on different databases, published literature and company’s drug information documents [6]. However, sufficient data cannot always be found during this search. In this situation, the data of another API with a similar chemical structure to the chemical under evaluation can be used to reach a suitable PDE. Establishing chemical similarity between the chemical under evaluation and the chemical which have sufficient toxicological data can give a chance to reach a PDE. Computational methods, such as read-across, have played an indispensable role in the progress of this idea. On the other hand, alternative methods, including computational methods, give a valuable contribution to the replacement, reduction, and refinement (3R initiatives) of experimental animal use in the predictive toxicology [8]. The regulatory bodies accept the use of read-across within analog or category approaches as a means of evaluating untested chemicals as part of a safety assessment [9]. In the read-across method, the endpoint information of a source chemical is utilized to predict the endpoint of another chemical (target chemical) or a group of structurally, metabolically or pharmacologically similar chemicals (Fig. 1) [10]. In this study, the category approach was applied to establish a common PDE value for a group of drug molecules that are structurally and metabolically similar.

Fig. 1.

a Category approach and b Analog approach. Filled marks represent the molecules with a known toxicity value (source chemical), while null marks represent the molecules without a toxicity value (target chemical)

Considering their similar structures and pathways, we appraised that nicotinic acid and its esters and also nicotinamide as a final metabolite could constitute a category for a read-across. Thus, it is possible to evaluate the toxicological endpoints of these compounds within the composed category.

This study aims to reach a sufficient PDE value which will be used for cleaning validation for nicotinic acid, nicotinate esters and nicotinamide based on available experimental data. The experimental data that were not available for a compound among the studied group were predicted using the category approach of the read-across method.

Materials and methods

Chemicals

Nicotinic acid and its esters (methyl, ethyl and benzyl nicotinate) and also nicotinamide were selected for the evaluation of their critical toxicological endpoint assessment and PDE calculation. The selected chemicals with their identity information are listed in Table 1.

Table 1.

The name, structure, Smiles, and CAS number of the selected compounds

Critical toxicological endpoints

Repeated dose toxicity, in vitro and in vivo mutagenicity test results representing genotoxicity, developmental/reproductive toxicity, carcinogenicity, and skin sensitization were considered critical toxicological endpoints according to EMA guideline [6].

Data collection and predictions

The experimental data for the considered endpoints were searched in the literature, PubChem (pubchem.ncbi.nlm.nih.gov), TOXNET (toxnet.nlm.nih.gov), ECHA (echa.europa.eu), EURL ECVAM (ec.europa.eu/jrc/en/eurl/ecvam), ISSSTY (Istituto Superiore di Sanità in vitro mutagenicity in Salmonella typhimurium) and ISSMIC (Istituto Superiore di Sanità in vivo mutagenicity (micronucleus test) databases [11], OECD QSAR Toolbox (v.4.1) (qsartoolbox.org), and Benchmark Data Set for in silico Prediction of Ames Mutagenicity of TU-Berlin (https://doc.ml.tuberlin.de/toxbenchmark/index.html#v2). Toxtree (v.3.1.0) [12], ToxRead (v.0.11) [13], VEGA-QSAR (www.vega-qsar.eu), US EPA TEST (v.4.2.1) [14], admetSAR (v.2) (https://lmmd.ecust.edu.cn/admetsar2), MouseTox for the prediction of cytotoxicity to mouse embryonic fibroblast NIH/3T3 cells [15], eMolTox [16], Labmole Pred-Skin (v.2.0) [17], XenoSite (v.1.0) [18], OECD QSAR Toolbox (qsartoolbox.org) and Danish QSARDB (https://qsardb.food.dtu.dk/db/index.html) were employed for the structural alerts and predictions. The US EPA EPI Suite (v.4.1) [19] and Drugbank (www.drugbank.ca) were used to obtain the physicochemical properties of the category members.

Establishing similarity

Similarity between the chemical under evaluation and the chemical which will be used for a prediction should be established in the first place. Category membership can be evaluated in many aspects. The basis for the similarity of category members was built primarily by structural similarity. The structural similarities were expressed as Tanimoto scores that were calculated employing their PubChem features in OECD QSAR Toolbox. In addition to the structural similarities, physicochemical property similarity, the presence of common structural alerts, and metabolism similarity were evaluated.

PDE calculation

According to the documents issued by EMA [6], PDE values for drug molecules produced in shared facilities were calculated using the following formula (Eq. 1). No observed adverse effect level (NOAEL) or lowest observed adverse effect level (LOAEL) for critical effects that were produced from experimental studies or by in silico methods were divided into a series of uncertainty factors (F1–5) to calculate PDE value.

$$\text{PDE}=\frac{\text{NOAEL}\left(\text{or LOAEL}\right)\times 50}{\text{F1}\times \text{F2}\times \text{F3}\times \text{F4}\times \text{F5}}$$ 1

F1 is (values between 2 and 12) uncertainties associated with estimating a human equivalent dose from animal studies [6, 20, 21], F2 is a factor of 10 to account for intraspecies variability [20–22], F3 is a factor (values between 1 and 10) to extrapolate from the short or subchronic exposure to daily exposure [23], F4 is a factor (values between 1 and 10) that may be applied in cases of severe toxicity [6, 24] and F5 is a variable factor that may be applied if the NOAEL was not established. When only LOAEL is available, a factor of up to 10 could be used depending on the severity of the toxicity [20]. 50 is the body weight according to the EMA document (6).

Results and discussion

Category formation

The category includes nicotinic acid, nicotinamide and nicotinate esters. The hypothesis in the category formation is that the members share similar molecular features, the same types of effects, and undergo similar pathways having their metabolites produced by the same mechanisms.

Structural and property similarity

Endpoint values for most of the physicochemical properties were predicted values by EPI Suite v 4.1. As seen in the data matrix (Table 2), the category members share similar properties. They are also structurally similar, proven by their high Tanimoto similarity scores calculated from their PubChem features (Table 3). Moreover, the structural alerts, such as protein and DNA binding, alerts for genotoxicity and skin sensitization related to the selected toxicological endpoints are consistent among the category members (Table SI).

Table 2.

Physicochemical properties of the category members

	Log P	Boiling point (C°)	Melting point (C°)	Vapor pressure (Pa)	Water solubility (mg L−1)
Nicotinic acid	0.36 0.69 (pred)	257.62 (pred)	236.6 63.27 (pred)	0.0125 (pred)	1.8e + 4 9678.1 (pred)
Nicotinamide	− 0.37 − 0.45 (pred)	157 297.54 (pred)	130 99.37 (pred)	0.0264 (pred)	5e + 5 1e + 6 (pred)
Methyl nicotinate	0.83 0.64 (pred)	204 205.25 (pred)	42.5 20.98 (pred)	25 (pred)	4.76e + 4 6.4241e + 5 (pred)
Ethyl nicotinate	1.32 1.13 (pred)	224 224.47 (pred)	8.5 32.23 (pred)	14.2 (pred)	5.6e + 4 2.0563e + 5 (pred)
Benzyl nicotinate	2.40 2.35 (pred)	170 324.14 (pred)	93.68 (pred)	0.0155 (pred)	3668.6 (pred)

Experimental if not noted otherwise

Table 3.

Tanimoto structural similarity indices as percent (as calculated in OECD QSAR Toolbox)

	Nicotinic acid	Nicotinamide	Methyl nicotinate	Ethyl nicotinate	Benzyl nicotinate
Nicotinic acid	1	0.82	0.93	0.90	0.86
Nicotinamide		1	0.81	0.79	0.76
Methyl nicotinate			1	0.97	0.91
Ethyl nicotinate				1	0.94
Benzyl nicotinate					1

Metabolic similarity

The compounds in the category demonstrate similarity in their pharmacological effect. Nicotinate esters are rapidly hydrolyzed to yield nicotinic acid. Data are scarce on the pharmacodynamics of nicotinate esters. However, it has been assumed that the close similarities between nicotinate esters, nicotinic acid and nicotinamide concerning structural and pharmacological properties also could indicate similar metabolism [25].

Their CYP-mediated sites of metabolisms were predicted using XenoSite (v.1.0) [18]. All category members were found to be metabolized using CYP3A4 and human liver microsomes (HLM) at the same sites (Nitrogen on the ring). Additionally, binding sites (the carbon between nitrogen and acid) to glutathione appeared to be the same. We concluded that these members are metabolically similar enough to form a category.

Toxicological endpoints

The experimental toxicity values of the studied compounds were culled from the sources listed in the data collection and predictions section, which are summarized in Table SI. The structural alerts and predictions for the category members were obtained using available software listed in the same section and are given in Table SI.

Repeated dose toxicity

Repeated dose oral toxicity data were available for nicotinamide and nicotinic acid, but not for its esters after the search in data collection tools, which were mentioned in “Materials and methods” section.

NOAEL values obtained from related repeated dose toxicity test data are placed in Table 4. PDE values from different repeated dose toxicity studies were calculated using Eq. (1) in this study [26–30].

Table 4.

Experimental repeated dose toxicity data, uncertainty factors, and PDE values of nicotinic acid and its esters and nicotinamide calculated by using repeated dose toxicity test data

Species	Dog, orala 2 months study	Rat, orala 2 months study	Rat, orala 1 month study	Rat, oralb 1 month study	Rat, orala 1 month study	Rat, orala 3 months study	Human, orala 3 years study
NOAEL (mg/kg/day)	2000 [27]	2000 [27]	215 [26]	1000 [28]	–	200 [29]	25 [30]
LOAEL (mg/kg/day)	–	–	–	–	1000g	–	–
F1	2	5	5	5	5	5	1
F2	10	10	10	10	10	10	10
F3	10	10	10	10	10	5	1
F4	1	1	1	1	1	1	1
F5	1	1	1	1	10	1	1
PDEc (mg/day)	500	200	21.5	100	10	40	125

The selection of F factors which is suitable for NOAEL or LOAEL data is based on explanation in Materials and method section

^aData belongs to nicotinamide

^bData belongs to nicotinic acid

^cBody weight is 50 kg

Genotoxicity

Nicotinamide was not mutagenic in bacterial strains with and without metabolic activation and did not induce clastogenic effects in both in vitro and in vivo micronucleus assays in mice [31].

The genotoxicity was searched on the databases EURL ECVAM Genotoxicity & Carcinogenicity Consolidated Database of Ames Positive Chemicals, Benchmark Data Set for in silico Prediction of Ames Mutagenicity of TU-Berlin, and ISSSTY (Ames) and ISSMIC (Micronucleus) databases (Table SI). ECHA reported that nicotinamide was negative in an in vivo genotoxicity test, and methyl nicotinate was negative in an in vitro test.

Based on the prediction made using the ToxRead considering the five closest analog substances to the query compound, gene mutation was predicted for all compounds under study. All of the predictions resulted in overall negative considering the most similar analog compounds. US EPA TEST and VEGA platform was employed for Ames mutagenicity predictions. The programs reported negative experimental values for nicotinic acid and nicotinamide. Moreover, they were predicted as negative for the rest of the compounds. Other predictions made using iPrior, admetSAR, Protox II, and pkCSM programs also resulted in negative for Ames (Table SI). admetSAR also predicted all compounds as negative for the micronucleus test, except nicotinamide with a low probability of 65%.

Gene mutation toxicities were searched and predicted for the compounds studied using the battery approach from the Danish QSAR Database (https://qsar.food.dtu.dk) using three software systems Leadscope, CASE Ultra and SciQSAR. The study assumed the use of Salmonella typhimurium bacteria in the Ames test. In the Danish QSAR Database platform, nicotinamide was reported to be Ames negative. Other compounds in the category were predicted not to induce mutation in Salmonella typhimurium by the Ames assay. Only nicotinamide had experimental values for other in vitro and in vivo genotoxicological endpoints. The majority of the predictions were negative (Table SI).

Based on the negative experimental results available for the category members and the presence of predominantly negative predictions, nicotinic acid and its esters and nicotinamide in the category do not introduce genotoxicity hazard. Hence, the value of zero was selected for uncertainty factor four (F4) regarding genotoxicity for PDE calculation.

Carcinogenicity

There were no reported studies of the carcinogenicity of methyl, ethyl and benzyl nicotinate. Additionally, nicotinic acid and nicotinamide had no positive carcinogenicity results in the databases (Table SI). The experimental carcinogenicity reports address some aspect of the carcinogenicity of nicotinamide in combination with other agents such as 9,10-dimethyl-12-benzanthracene [32], streptozotocin [33], and diethylnitrosamine [34]. Only one study evaluated the carcinogenicity of nicotinamide alone [35]. In that study, the carcinogenic potential of 66.3 and 100.5 mg/day nicotinamide by the oral route was investigated in female and male mice for their life span, respectively. The treatment had no carcinogenic effect when compared to untreated controls.

admeSAR and Protox II predicted all compounds as negative. VEGA platform has several models. Some predicted positive, while some predicted negative (with low reliability). eMolTox predicted carcinogenic activity either negative or inconclusive for mice (Table SI). CASE Ultra and Leadscope software predictions, developed using the male/female rat and mouse; and rodent experimental carcinogenicity data from the US Food and Drug Administration as part of the Research Cooperation Agreement, are available in the Danish QSAR Database. The inconclusive and out-of-applicability domain predictions were not reported in Table SI.

According to the data above, nicotinic acid and its esters and nicotinamide in the category are not carcinogenic and the value of zero was selected for F4 regarding carcinogenicity for PDE calculation (Table 5).

Table 5.

PDE values of nicotinic acid and its esters and nicotinamide calculated by using carcinogenicity data

Species	Rat, orala Life span
	Male	Female
NOAEL (mg/kg/day)	100.5 [35]	66.3 [35]
F1	5	5
F2	10	10
F3	1	1
F4	1	1
F5	1	1
PDEb (mg/day)	100.5	66.3

The selection of F factors which is suitable for NOAEL or LOAE data is based on explanation in materials and method section

^aData belongs to nicotinamide

^bBody weight is 50 kg

Developmental and reproductive toxicity

The predictions for the studied compounds were resulted in negative using various models. US EPA TEST program predicted methyl, ethyl and benzyl nicotinate as negative for developmental toxicity. Nicotinic acid and nicotinamide were predicted as negative. Additionally, these compounds were reported to have negative experimental values obtained from the CAESAR project. The VEGA predictions for all compounds were also negative for developmental toxicity. Teratogenic potentials of category members in humans were predicted in the Danish QSAR Database. The battery predictions appeared to be negative, except benzyl nicotinate, whose prediction was inconclusive (Table SI).

Based on the negative experimental results available for the category members and the presence of predominantly negative predictions, nicotinic acid and its esters and nicotinamide in the category are not teratogenic. PDE calculation was performed according to factors reported in Table 6 using NOAEL value from developmental and reproductive toxicity data [31].

Table 6.

PDE value calculated by using reproductive and developmental toxicity data for nicotinic acid and its esters and nicotinamide

Species	Rat, orala Development toxicity including whole organogenesis period
NOAEL (mg/kg/day)	200 [31]
F1	5
F2	10
F3	1
F4	1
F5	1
PDEb (mg/day)	200

The selection of F factors which is suitable for NOAEL or LOAE data is based on explanation in materials and method section

^aData belongs to nicotinic acid

^bBody weight is 50 kg

Skin sensitization

No indication of the dermal sensitization of nicotinamide was reported in guinea pig studies. However, it was considered to be irritating to the eyes when tested on rabbits [31]. In a study, the skin sensitizing potential of methyl nicotinate was evaluated in the guinea pig using ear swelling test. A group of five female animals was challenged by applying 50 µL of various concentrations of methyl nicotinate concentrations to both sides of the earlobe. The thickness of the ear was measured with a string micrometer before application and at five to 30 min intervals thereafter. Methyl nicotinate was found to be non-sensitizing in female Hartley strain guinea pigs [36].

Labmol Pred-skin predictions were made on human skin sensitization, murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), and human cell line activation test (h-CLAT). The overall predictions for nicotine amide were positive; however, other compounds were negative. pkCSM software predicted all compounds as skin sensitizers, except benzyl nicotinate. VEGA predicted benzyl nicotinate as positive and others as negative.

Overall evaluation of PDE calculation

Based on the read-across data, nicotinic acid and its esters and also nicotinamide are not genotoxic and do not have skin sensitization potential. Also, these compounds do not present a concern for carcinogenicity, teratogenicity, developmental and reproductive toxicity. According to the available published data listed above, calculated PDE values are seen in Table 4, 5 and 6, respectively. According to these calculated PDE values, the final PDE value was established as 10 mg/day for nicotinic acid and its esters and also nicotinamide.

Statement of uncertainty

In this read-across study, the uncertainty is evaluated with some types of measurements and evaluations. Structural and biological similarities were considered in category formation. Adequate evidence supporting the similarity hypotheses were presented. Chemicals selected in the category have similar structural and physicochemical properties (Table 2, 3), leading to similar bioavailability and metabolism. Experimental data were obtained from scientific publications and reports cited above and had a good reliability. Therefore, the predictions for the endpoints have a low uncertainty due to these high similarities between the category members and reliable experimental data.

Conclusion

There are insufficient toxicity data on nicotinic acid and its esters methyl, ethyl and benzyl nicotinate, and nicotinamide. However, available data on compounds within the established category could be used to predict these endpoints. Based on the current existing data, nicotinic acid and its esters and also nicotinamide are not genotoxic and do not have skin sensitization potential. Additionally, these compounds do not present a concern for carcinogenicity, teratogenicity, developmental, and reproductive toxicity. Based on these critical endpoints and available experimental data, the final PDE of 10 mg/day was calculated for all category members studied in this study. Our study showed the utility of read-across approach in PDE calculation of APIs with experimental toxicological data gap. Applying the read-across methods to structurally similar chemicals gives permission to calculate PDE values, which will be used for cleaning validation for the production equipment in pharmaceutical companies.

Electronic supplementary material

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Compliance with ethical standards

Conflict of interest

The authors report no conflict of interest.