Simultaneous detection of 24 oral antidiabetic drugs and their metabolites in urine by liquid chromatography–tandem mass spectrometry

Journal Pre-proofs Simultaneous detection of 24 oral antidiabetic drugs and their metabolites in urine by liquid chromatography–tandem mass spectrometry Ying Hoo Lam, Mei Tik Leung, Chor Kwan Ching, Tony Wing Lai Mak PII: DOI: Reference:

S1570-0232(19)30894-3 https://doi.org/10.1016/j.jchromb.2020.122020 CHROMB 122020

To appear in:

Journal of Chromatography B

Received Date: Revised Date: Accepted Date:

14 June 2019 10 December 2019 2 February 2020

Please cite this article as: Y. Hoo Lam, M. Tik Leung, C. Kwan Ching, T. Wing Lai Mak, Simultaneous detection of 24 oral antidiabetic drugs and their metabolites in urine by liquid chromatography–tandem mass spectrometry, Journal of Chromatography B (2020), doi: https://doi.org/10.1016/j.jchromb.2020.122020

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© 2020 Published by Elsevier B.V.

Simultaneous detection of 24 oral antidiabetic drugs and their metabolites in urine by liquid chromatography–tandem mass spectrometry

Ying Hoo Lam1, Mei Tik Leung2, Chor Kwan Ching1, Tony Wing Lai Mak1

1Hospital

Authority Toxicology Reference Laboratory, Princess Margaret Hospital,

Hong Kong

2Department

of Pathology, Queen Elizabeth Hospital, Hong Kong

*Corresponding author: Dr Tony Wing Lai Mak

Postal address: Room 1414, Block G, Princess Margaret Hospital, Lai Chi Kok, Kowloon, Hong Kong

Tel.: +852 29901987

Fax: +852 29901942

E-mail address: [email protected]

1

Abstract:

Drugs are the most frequent cause of hypoglycemia. Though the drug history is usually obvious in diabetic patients, the diagnosis could be a challenge in patients without a history of such exposure. Screening for oral antidiabetic drugs has been recommended as part of the hypoglycemia workup in patients without diabetes. Many published analytical methods of oral antidiabetic agents were usually of limited coverage and restricted to parent drugs only. In the current study, a liquid chromatography–tandem mass spectrometry (LC-MS/MS) analytical system for the simultaneous detection of 24 oral antidiabetic drugs and their metabolites in urine was established and validated. The method covered both conventional as well as the newer antidiabetic drugs such as dipeptidyl peptidase-4 inhibitors and sodium-glucose cotransporter-2 inhibitors. Following sample preparation by solid phase extraction, analytes were detected by LC-MS/MS with multiple reaction monitoring triggered enhanced product ion scan. The method was successfully applied to 233 cases of unexplained hypoglycemia, with 83 oral antidiabetic drugs detected in 51 of the urine samples.

Keywords: 2

Oral antidiabetic drug; Drug-induced hypoglycemia; LC-MS/MS; Urine analysis; Drug screening

Abbreviations:

LC-MS/MS, liquid-chromatography tandem mass spectrometry; IS, internal standard; ACN, acetonitrile; DMSO, dimethyl sulfoxide; QC, quality control; LOD, limit of detection; MP, mobile phase; MRM, multiple reaction monitoring; IDA, information dependent acquisition; RT, retention time; DPP-4, dipeptidyl peptidase-4; SGLT-2, sodium-glucose cotransporter-2

3

1. Introduction

Hypoglycemia is a potentially fatal yet readily correctable condition, and it is important to identify the underlying etiology. Drugs, especially insulin or insulin secretagogues, are the most common cause of hypoglycemia among others [1]. The landscape of glycemic management for type 2 diabetes has significantly changed over the past two decades, and there are now 12 different classes of antidiabetic drugs available [2]. Though the newer antidiabetic agents are expected typically not to cause hypoglycemia, a recent study showed that the overall rate of severe hypoglycemia remained largely unchanged despite the increase in utilization of the newer agents [3]. The cause of hypoglycemia is usually obvious in diabetic patients taking glucose lowering drugs. However, determining the etiology of hypoglycemia could be a challenge in patients without a history of such exposure. Screening for oral antidiabetic drugs has been recommended as part of the hypoglycemia workup in patients without diabetes [1]. As the only tertiary clinical toxicology laboratory in Hong Kong, our group has previously detected oral antidiabetic drugs in numerous cases of hypoglycemia without known history of drug exposure, with sources including drug administration errors, drug intake by mistake, and proprietary Chinese medicines adulterated with oral antidiabetic drugs [4-6]. This highlighted the importance of laboratory detection of oral antidiabetic agents in patient samples. 4

A number of analytical methods have been published for the detection and quantitation of oral antidiabetic agents in human biological samples and in drugs for counterfeit analysis, but the coverage was usually limited and restricted to parent drugs [7-16]. As many oral antidiabetic drugs are rapidly and extensively metabolized, the detection of these metabolites in urine sample is of paramount importance in identifying subjects with accidental or surreptitious drug use. At present, comprehensive and simultaneous testing for conventional and new oral antidiabetic drugs in human urine is not widely available in most clinical laboratories.

The current study aimed to develop a sensitive and selective liquid chromatography – tandem mass spectrometry (LC-MS/MS) method for simultaneous analysis of 24 oral antidiabetics and their metabolites in human urine, which allowed reliable and robust detection of both conventional as well as the newer antidiabetic drugs. The method was validated according to international guidelines [17-18] and subsequently applied in analysis of patient urine samples with unexplained hypoglycemia.

2. Materials and methods 2.1 Reagents

Reference standards of acetohexamide (internal standard (IS)), gliquidone, metformin, nateglinide were obtained from International Laboratory USA 5

(San Francisco, USA); alogliptin, canagliflozin, dapagliflozin, ipragliflozin, linagliptin, repaglinide, saxagliptin, sitagliptin and vildagliptin were obtained from TRC (Toronto, Canada); chlorpropamide was obtained from TCI (Tokyo, Japan); empagliflozin was obtained from Selleckchem (Houston, TX, USA); glibenclamide, glimepiride and phenformin were obtained from SigmaAldrich (Saint Louis, MO, USA); gliclazide was obtained from LKT Laboratories (Saint Paul, MN, USA); glipizide, pioglitazone and rosiglitazone were obtained from Alexis Biochemicals (San Diego, California, USA); tofogliflozin was obtained from MedChem Express (NJ, USA); tolazamide and tolbutamide were obtained from Wako Pure Chemical (Osaka, Japan). Acetonitrile (ACN) and methanol of LCMS grade were purchased from J.T. Baker (Deventer, The Netherlands) and Duksan (Kyunggi, Korea) respectively. Ammonium formate and dimethyl sulfoxide (DMSO) were purchased from Fluka (Buchs, Switzerland) and SigmaAldrich (Saint Louis, MO, USA) respectively. Formic acid was purchased from Merck (Darmstadt, Germany). Oasis® HLB cartridge was obtained from Waters Corporation (Milford, MA, USA). Certified drug-free urine was obtained from UTAK Laboratories (Valencia, CA, USA). Purified water was provided by Elga Purelab Flex III Water Purification System (High Wycombe, UK). 6

2.2 Preparation of standards and quality control materials

Stock standard solutions (1 mg/mL) of each analyte were prepared in methanol or DMSO. Intermediate standard mix (0.1 mg/mL) was prepared in methanol by adding individual standards. All standards or intermediate standard mix were stored at 4C. The intermediate standard mix was spiked to drug-free urine to produce positive quality control (QC) material at a concentration of 120% of the limit of detection (LOD). Drug-free urine also served as the negative QC material. All QC materials were stored at −70C.

Stock IS solution (1 mg/mL) in methanol was stored at 4C. Working IS (0.1 mg/mL) was prepared in purified water/methanol (50:50, v/v) and stored at 4C.

2.3 Sample preparation

The sample was cleaned up by solid phase extraction on a Biotage Pressure+ 48 positive pressure manifold (Uppsala, Sweden). Oasis® HLB cartridges (3 cc, 60 mg) were conditioned with 2 mL methanol followed by 2 mL purified water. 1 mL urine sample, with 50 L of working IS added, was loaded onto the cartridge, which was then washed with 2 mL purified water/methanol (95:5, v/v). The sample was finally eluted with 2 mL methanol. The eluate was 7

evaporated to dryness under a stream of nitrogen at 45C. The dried residue was reconstituted with 0.2 mL of purified water/formic acid/1 M ammonium formate/ACN (80:0.2:0.2:20, v/v). Subsequently, 0.2 mL of purified water/formic acid/1 M ammonium formate (100:0.2:0.2, v/v) was added to mix with the sample.

2.4 LC-MS/MS analysis

Chromatographic separation was performed on an Agilent 1200 Series LC system (Santa Clara, CA, USA) equipped with Agilent Zorbax Eclipse XDB C8 column (150 mm × 4.6 mm i.d., 5 m particle size). The mobile phase consisted of 2 mM ammonium formate and 0.2% formic acid in purified water (mobile phase A, MPA) and 2 mM ammonium formate and 0.2% formic acid in ACN (mobile phase B, MPB). The gradient program started with 10% MPB, changed linearly to 80% MPB over 10 minutes and maintained until 15 minutes. Subsequently, the MPB content was reverted to 10% at 16 minutes and held until 20 minutes. The total run time was 20 min; the flow rate was 0.5 mL/min and the injection volume was 10 L.

MS/MS analysis was performed in the positive electrospray ionization mode on an Applied Biosystems MDS SCIEX 3200 QTRAP LC-MS/MS system 8

(Foster City, CA, USA). The following instrument-dependent parameters were applied: ion spray voltage of 3000 V, source temperature of 600C, curtain gas of 15 arbitrary units, collision gas of high, ion source gas 1 of 50 arbitrary units and ion source gas 2 of 50 arbitrary units. Multiple reaction monitoring (MRM) transitions were used to trigger an enhanced product ion scan in an information dependent acquisition (IDA) experiment with mass spectral library search. One MRM transition per analyte was used in MS acquisition. For the parent drugs, compound optimization was performed by direct infusion of the reference standards, and the MRM transition with the most abundant response was selected to set up the method. For the metabolites, MRM transitions and product ion scan spectra were gathered from various publications [8-16]. The retention time and product ion spectra of the metabolites for library entry were obtained from analysis of urine samples collected from subjects with known drug history. The optimized compounddependent parameters of the analytes were shown in Table 1.

Each transition was performed with scheduled MRM and pause time of 5 ms. MS/MS spectra were registered at collision energy of 32 V and collision energy spread of 15 V. The IDA scan intensity threshold was set to 1,000 cps. Dynamic exclusion of 5 s after 2 occurrences of former target ions and the 9

mass tolerance of 250 mDa were applied. Fragments generated in the product ion spectra were detected in the range between 55 and 650 amu with dynamic fill time and a scan rate of 4,000 Da/s, and the resolution of Q1 device was set to unit. The presence of analyte in the urine was confirmed by both the retention time (RT) and a good matching of analyte spectra in the samples to the reference spectra with critical match factor (Fit, RevFit and Purity) above 60%.

2.5 Assay Validation

This method was validated according to the approved Clinical and Laboratory Standard Institute (CLSI C50-A) guideline [17] and EURACHEM (A Focus for Analytical Chemistry in Europe) guideline [18]. Full validation was performed for the parent drugs, while only limited validation, including selectivity, specificity and verification with authentic urine samples, could be performed for the metabolites due to the unavailability or high cost of their reference standards.

2.5.1

Selectivity

Urine samples from 10 patients without history of taking oral antidiabetic drugs and 1 urine sample of normal subject spiked with 10

Ceriliant interference mixture (containing 28 western medications) were analyzed for any interfering compounds.

The 28 medications in the interference mixture included cotinine, nicotine, acetaminophen, caffeine, ibuprofen, naproxen, phentermine, pseudoephedrine, alprazolam, cimetidine, citalopram, clopidogrel, dextromethorphan, fluconazole, hydrochlorothiazide, lamotrigine, thyroxine, methylphenidate, omeprazole, amlodipine, atorvastatin, azithromycin, bupivacaine, cetirizine, dimenhydrinate, lisinopril and loratadine.

2.5.2

LOD

LOD was determined by spiking 10 normal urine blanks with each analyte at a range of 5 concentration levels. Various levels were randomized during analysis. The lowest concentration with 100% positive results based on the aforementioned identification criteria was defined as the LOD.

2.5.3

Repeatability, reproducibility and retention time precision

Repeatability (within-run precision) was evaluated by testing urine 11

blank spiked with analytes at the corresponding LOD level in 6 replicates in the same run. Reproducibility (between-run precision) was evaluated by testing urine blank spiked with analytes at the corresponding LOD level in 3 replicates per run for 5 different days. The retention time precision of the analytes over the validation period was also monitored and expressed in relative standard deviation.

2.5.4

Sensitivity and specificity

10 urine samples collected from patients that did not take antidiabetic drugs were analyzed. False positive rate was determined as: False positives / Total known negatives x 100%. Specificity rate was determined as: Test negatives / Total known negatives x 100%.

10 urine samples from healthy volunteers spiked with analytes at LOD plus 20% level were analyzed. False negative rate was determined as: False negatives / Total known positives x 100%. Sensitivity rate was determined as: Test positives / Total known positives x 100%.

2.5.5

Extraction recovery and matrix effect

Matrix-free solvent was spiked with the analytes at the LOD levels 12

(Set A). Two sets of normal urine blanks from 6 different sources were spiked with the analytes at the LOD levels before extraction (Set B) and after extraction (Set C) respectively. The extraction recovery and matrix effect of individual analytes were calculated as follows:

Extraction recovery = peak area of set B / peak area of set C x 100%

Matrix effect = peak area of set C / peak area of set A x 100%

2.5.6

Carryover

Carryover was evaluated by testing two blank samples before and after a sample spiking with high concentration of the target analytes at 100fold of the LOD. Carryover rate was calculated as [(peak area of blank sample after high concentration sample – peak area of blank sample before high concentration sample) / peak area of high concentration sample] x 100%.

2.5.7

Stability

3 blank urine samples spiked with analytes at LOD levels were stored at room temperature for 7 days and 4°C for 14 days until analysis to test for sample stability. 13

Post-preparative stability was also assessed to decide whether prepared samples could be re-injected during instrument failure. 3 processed samples with analytes at LOD levels were injected for 10 consecutive days. The processed samples were stored at room temperature during the evaluation. Analytes were deemed stable if they could be detected by the identification criteria following the storage period.

2.5.8

Validation with authentic urine samples

Urine samples collected from 15 subjects who have taken various oral antidiabetic drugs were analyzed to verify the present method.

2.6 Application to clinical toxicology service

The validated method was applied to analysis of patient samples with unexplained hypoglycemia. From Jul 2017 to Dec 2018, 233 cases of unexplained hypoglycemia were referred to the authors’ laboratory for testing of oral antidiabetic drugs. Urine samples were stored at 4°C before analysis.

3. Results and discussion 3.1 Method development

We developed a LC-MS/MS method for comprehensive detection of 24 oral 14

antidiabetic drugs and their metabolites, including drug classes of biguanides, dipeptidyl peptidase-4 (DPP-4) inhibitors, glitazones, meglitinides, sodiumglucose cotransporter-2 (SGLT-2) inhibitors and sulfonylureas. The chemical structures of the 24 oral antidiabetic drugs and IS were shown in Figure 1. Urine was the preferred specimen type because of the longer detection window compared with blood, especially with the inclusion of metabolites in the coverage. Solid phase extraction by Oasis® HLB sorbent with a hydrophilic-lipophilic balance was used to allow retention of both polar (e.g. biguanides) and non-polar analytes. The chromatographic conditions in this method provided satisfactory separation for the majority of the analytes, and compound identification by both retention time and MRM-triggered enhanced product ion scan with library matching provided high analytical specificity. A representative chromatogram of the 24 oral antidiabetic drugs and IS was shown in Figure 2.

3.2 Method validation

The method was validated for the 24 parent drug analytes for selectivity, LOD, repeatability, reproducibility, retention time precision, sensitivity, specificity, extraction recovery, matrix effect, carryover effect and stability. The

15

validation results on LOD, retention time precision, extraction recovery and matrix effect were summarized in Table 2.

The method was selective for all analytes, as shown by the absence of interference peaks in the 10 urine samples collected from patients with no known antidiabetic drug intake and 1 blank urine sample spiked with interference mixture.

The LOD for all analytes ranged between 5 – 500 ng/mL. 17 out of 24 analytes (71%) had LOD of 50 ng/mL or below, whereas sodium-glucose cotransporter-2 inhibitors, metformin, chlorpropamide and gliquidone had higher LOD of 200 – 500 ng/mL. The method showed 100% repeatability and reproducibility, with all analytes positively identified in the within-run and between-run replicates. The retention time relative standard deviation of all analytes was <0.5%. Analyses of 10 urine samples collected from patients who did not take antidiabetic drugs were all negative for the target compounds, hence false positive rate was 0% (100% specificity) for all analytes. False negative rate at LOD level plus 20% was 0% (100% sensitivity) for all analytes. The urine extraction recovery was more than 70% for all analytes except metformin. Considering the polar nature, the low

16

recovery (24%) and relatively high LOD (500 mg) of metformin in this method is still considered acceptable. Given that metformin is usually used in high dosage ranged from 250 mg to 1000 mg, the developed method can meet the required level of sensitivity for detection of metformin in urine. The urine matrix effects of the analytes ranged from 32% to 152%. Majority of the analytes (21/24; 88%) had satisfactory matrix effect of more than 68% except phenformin, rosiglitazone and pioglitazone. Higher ion suppression was observed in phenformin, rosiglitazone and pioglitazone, with urine matrix effects of 33%, 33% and 32% respectively. It is still considered acceptable since a low LOD at 10 ng/mL could be achieved for these analytes. No carryover was observed for all analytes at 100 fold of the LOD. All analytes were found to be stable in urine at room temperature for 7 days and 4°C for 14 days. The post-preparative stability was up to 9 days when samples were stored at room temperature on the autosampler.

In the 15 urine samples collected from subjects who have taken 1 or more oral antidiabetic drugs including biguanides (metformin, n=10), DPP-4 inhibitors (linagliptin, n=3; sitagliptin, n=3; vildagliptin, n=2), glitazones (pioglitazone, n=4), SGLT-2 inhibitors (canagliflozin, n=2; dapagliflozin, n=2; empagliflozin, n=4) and sulfonylureas (gliclazide, n=8; glimepiride, 17

n=1), all results were concordant with the patients’ drug history except that empagliflozin was detected in only 3 out of 4 urine samples. There were two possible reasons for the negative result in the remaining sample: either the LOD of empagliflozin (300 ng/mL) or its metabolites (not studied) was not sensitive enough for the detection in that particular urine sample; or poor patient compliance to the drug.

3.3 Application to clinical toxicology service

The validated method with expanded coverage has been put into clinical service since Jul 2017. From Jul 2017 to Dec 2018, a total of 233 cases of unexplained hypoglycemia were referred to the authors’ laboratory for urine testing of oral antidiabetic drugs. 83 oral antidiabetic drugs were detected in 51 of the urine samples (22%), including gliclazide (n=34), metformin (n=25), glibenclamide (n=5), glimepiride (n=4), phenformin (n=3), pioglitazone (n=3), rosiglitazone (n=2), linagliptin (n=2), sitagliptin (n=2), alogliptin (n=1), vildagliptin (n=1) and glipizide (n=1). Laboratory testing of oral antidiabetic drugs in urine samples of patients with unexplained hypoglycemia played an indispensable role in identifying accidental or surreptitious drug use as part of the work up.

18

4. Conclusion

A sensitive and specific LC-MS/MS method for simultaneous detection of 24 oral antidiabetic drugs and their metabolites in urine samples has been established and validated. The method was successfully applied in clinical toxicology service to facilitate investigation of unexplained hypoglycemia cases.

Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Figure caption

Figure 1 Chemical structures of the 24 oral antidiabetic drugs and internal standard.

Figure 2 Representative chromatogram of a mixture containing the 24 oral antidiabetic drugs and internal standard. Metformin (1), vildagliptin (2), saxagliptin (3), phenformin (4), alogliptin (5), linagliptin (6), rosiglitazone (7), sitagliptin (8), pioglitazone (9), empagliflozin (10), tofogliflozin (11), ipragliflozin (12), dapagliflozin (13), glipizide (14), canagliflozin (15), chlorpropamide (16),

19

acetohexamide (internal standard; 17), tolbutamide (18), repaglinide (19), tolazamide (20), gliclazide (21), glibenclamide (22), glimepiride (23), nateglinide (24) and gliquidone (25).

20

Table 1 LC-MS/MS parameters of the analytes. Drug class

Biguanides

Dipeptidyl peptidase-4 inhibitors

Analyte

MRM

RT

DP

EP

CE

CXP

transition

(min)

(V)

(V)

(V)

(V)

Metformin

130.1/71.1

3.0

31

5

25

4

Phenformin

206.2/60.1

8.1

41

5

27

4

Phenformin Hydroxy metabolite

222.1/121.2

5.0

41

8

29

4

Alogliptin

340.2/116.2

8.4

67

9

47

4

Linagliptin

473.3/420.1

9.2

91

9

29

4

Saxagliptin

316.2/180.1

8.1

66

8

27

3

Sitagliptin

408.2/235.2

9.4

66

8

27

4

Vildagliptin

304.2/154.1

7.3

62

6

23

3

21

Glitazones

Meglitinides

Sodium-glucose cotransporter-2

Vildagliptin Carboxy metabolite

323.2/173.2

7.0

62

6

27

3

Pioglitazone

357.1/134.1

9.9

56

5

37

4

Pioglitazone Hydroxy metabolite I

373.3/150.1

8.8

61

11

37

4

Pioglitazone Hydroxy metabolite II

373.2/239.1

9.4

56

8

35

4

Rosiglitazone

358.1/135.2

9.3

56

5

35

4

Rosiglitazone Hydroxy metabolite

374.0/151.1

9.0

61

12

29

4

Rosiglitazone Desmethyl metabolite

344.2/121.1

8.9

61

12

33

4

Nateglinide

318.2/166.1

14.7

41

5

19

4

Repaglinide

453.3/230.3

13.0

51

5

37

4

Repaglinide Hydroxy metabolite

469.3/246.2

13.3

51

9

33

4

Canagliflozin ammonia adduct

462.1/191.1

12.4

48

7

41

3

22

inhibitors

Canagliflozin glucuronide I ammonium

638.1/349.1

10.7

22

10

30

3

638.2/349.1

11.6

22

10

30

3

Dapagliflozin ammonium adduct

426.3/135.2

11.5

50

8

23

2

Dapagliflozin glucuronide I ammonium

602.1/355.1

9.8

27

10

30

3

602.2/355.1

10.8

27

10

30

3

Empagliflozin ammonium adduct

468.2/355.2

10.6

41

7

18

5

Empagliflozin glucuronide I ammonium

644.2/355.1

9.7

20

10

30

3

adduct Canagliflozin glucuronide II ammonium adduct

adduct Dapagliflozin glucuronide II ammonium adduct

23

adduct Empagliflozin glucuronide II

644.2/355.2

10.3

20

10

30

3

Ipragliflozin ammonium adduct

422.2/151.2

11.4

58

6

33

3

Tofogliflozin

387.2/267.1

11.2

73

7

19

4

Acetohexamide (IS)

325.2/243.1

12.9

51

11

17

4

Chlorpropamide

277.1/111.1

12.7

41

5

45

4

Glibenclamide

494.1/369.2

14.2

46

5

25

6

Glibenclamide Hydroxy metabolite I

510.0/369.2

11.5

41

9

25

6

Glibenclamide Hydroxy metabolite II

510.1/369.1

11.8

41

9

25

6

Gliclazide

324.1/127.2

13.9

56

5

25

4

ammonium adduct

Sulfonylureas

24

Gliclazide Hydroxy metabolite I

340.0/127.2

11.3

56

5

25

4

Gliclazide Hydroxy metabolite II

340.0/143.2

10.5

56

5

25

4

Glimepiride

491.2/352.2

14.5

46

5

23

6

Glimepiride Hydroxy metabolite

507.2/352.2

11.3

46

9

21

6

Glimepiride Carboxy metabolite

521.3/352.2

11.6

51

8

21

6

Glipizide

446.2/321.0

12.3

41

5

23

6

Glipizide Hydroxy metabolite

462.0/321.0

9.4

41

5

23

6

Gliquidone

528.1/403.2

15.3

60

10

21

6

Tolazamide

312.1/115.3

13.4

51

5

25

4

Tolbutamide

271.1/155.0

13.0

36

11

23

4

Tolbutamide Hydroxy metabolite

287.2/171.1

10.6

46

11

23

4

25

Tolbutamide Carboxy metabolite

301.2/202.0

11.1

61

9

19

4

Table 2 Summary of validation results. Drug class

Analyte

Biguanides

Metformin

500

0.26

24 (942)

78 (6492)

Phenformin

10

0.33

108 (63127)

33 (1456)

Alogliptin

10

0.24

102 (73119)

136 (63206)

Linagliptin

10

0.23

97 (63110)

106 (57157)

Saxagliptin

10

0.26

99 (80116)

146 (102193)

Sitagliptin

10

0.23

91 (67102)

130 (92161)

Vildagliptin

10

0.35

115 (88130)

130 (71194)

Pioglitazone

10

0.25

89 (66103)

32 (1744)

Dipeptidyl peptidase-4 inhibitors

Glitazones

LOD (ng/mL) RT Precision (%RSD) Recovery (%) Matrix effect (%)

26

Rosiglitazone

10

0.22

85 (56101)

33 (1850)

Nateglinide

50

0.00

103 (92116)

109 (73191)

Repaglinide

5

0.39

94 (8598)

93 (9095)

Sodium-glucose cotransporter-2 inhibitors Canagliflozin

300

0.00

87 (7596)

91 (78108)

Dapagliflozin

500

0.22

107 (88116)

76 (57-86)

Empagliflozin

300

0.39

103 85116)

75 (4792)

Ipragliflozin

500

0.00

100 (86106)

68 (5180)

Tofogliflozin

50

0.37

106 (90114)

84 (54105)

Chlorpropamide

200

0.00

104 (92112)

96 (86107)

Glibenclamide

10

0.34

93 (80110)

83 (52173)

Gliclazide

10

0.35

110 (88126)

149 (129227)

Meglitinides

Sulfonylureas

27

Glimepiride

50

0.35

95 (84117)

102 (63202)

Glipizide

10

0.00

100 (78107)

152 (118199)

Gliquidone

200

0.23

81 (67109)

73 (43148)

Tolazamide

10

0.31

111 (87132)

149 (131207)

Tolbutamide

50

0.40

106 (85119)

103 (50124)

28

References: [1] P.E. Cryer, L. Axelrod, A.B. Grossman, S.R. Heller, V.M. Montori, E.R. Seaquist, F.J. Service, Evaluation and Management of Adult Hypoglycemic Disorders: An Endocrine Society Clinical Practice Guideline, J. Clin. Endocrinol. Metab. 94 (2009) 709-728. doi:10.1210/jc.2008-1410. [2] A. Chaudhury, C. Duvoor, V.S. Reddy Dendi, S. Kraleti, A. Chada, R. Ravilla, A. Marco, N.S. Shekhawat, M.T. Montales, K. Kuriakose, A. Sasapu, A. Beebe, N. Patil, C.K. Musham, G.P. Lohani, W. Mirza, Clinical Review of Antidiabetic Drugs: Implications for Type 2 Diabetes Mellitus Management, Front. Endocrinol. 8 (2017). doi:10.3389/fendo.2017.00006. [3] K.J. Lipska, X. Yao, J. Herrin, R.G. McCoy, J.S. Ross, M.A. Steinman, S.E. Inzucchi, T.M. Gill, H.M. Krumholz, N.D. Shah, Trends in Drug Utilization, Glycemic Control, and Rates of Severe Hypoglycemia, 2006–2013, Dia Care. 40 (2017) 468-475. doi:10.2337/dc16-0985. [4] C.K. Ching, C.K. Lai, W.T. Poon, M.C. Lui, Y.H. Lam, C.C. Shek, T.W.L. Mak, A.Y.W. Chan, Drug-induced hypoglycaemia–new insight into an old problem, Hong Kong Med J. 12 (2006) 334-8. [5] C.K. Ching, Y.H. Lam, A.Y.W. Chan, T.W.L. Mak, Adulteration of herbal antidiabetic products with undeclared pharmaceuticals: a case series in Hong 29

Kong, Br J Clin Pharmacol. 73 (2012) 795-800. doi:10.1111/j.13652125.2011.04135.x. [6] C.K. Ching, S.P.L. Chen, H.H.C. Lee, Y.H. Lam, S.W. Ng, M.L. Chen, M.H.Y. Tang, S.S.S. Chan, C.W.Y. Ng, J.W.L. Cheung, T.Y.C. Chan, N.K.C. Lau, Y.K Chong, T.W.L. Mak, Adulteration of proprietary Chinese medicines and health products with undeclared drugs: experience of a tertiary toxicology laboratory in Hong Kong, Br J Clin Pharmacol. 84 (2018) 172-178. doi:10.1111/bcp.13420. [7] Q.-K. Truong, X.-L. Mai, J.-Y. Lee, J. Rhee, D. Vinh, J. Hong, K.H. Kim, Simultaneous determination of 14 oral antihyperglycaemic drugs in human urine by liquid chromatography–tandem mass spectrometry, Arch. Pharm. Res. 41 (2018) 530-543. doi:10.1007/s12272-018-1011-9. [8] S. Kai, K. Ishikawa, H. Ito, T. Ogawa, H. Yamashita, Y. Nagata, H. Kanazawa, Simultaneous Analysis of Oral Antidiabetic Drug by LC-MS/MS, Chromatogr. 36 (2015) 19-24. doi:10.15583/jpchrom.2015.003. [9] P.A. Shah, J.V. Shah, M. Sanyal, P.S. Shrivastav, LC-MS/MS analysis of metformin, saxagliptin and 5-hydroxy saxagliptin in human plasma and its pharmacokinetic study with a fixed-dose formulation in healthy Indian subjects, Biomed. Chromatogr. 31 (2017) e3809. doi:10.1002/bmc.3809.

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[10] S. Mahamad Shafi, A. Begum, N. Saradhi, Bioanalytical method development and validation of linagliptin in plasma through LC-MS/MS, Int. J. Bioassays 3 (2014) 3146-3151. [11] S. Kobuchi, M. Matsuno, E. Fukuda, Y. Ito, T. Sakaeda, Development and validation of an LC–MS/MS method for the determination of tofogliflozin in plasma and its application to a pharmacokinetic study in rats, J. Chromatogr. B 1027 (2016) 227-233. doi:10.1016/j.jchromb.2016.05.053. [12] S. Kobuchi, K. Yano, Y. Ito, T. Sakaeda, A validated LC-MS/MS method for the determination of canagliflozin, a sodium-glucose co-transporter 2 (SGLT-2) inhibitor, in a lower volume of rat plasma: application to pharmacokinetic studies in rats, Biomed. Chromatogr. 30 (2016) 1549-1555. doi:10.1002/bmc.3720. [13] S. Kobuchi, Y. Ito, K. Yano, T. Sakaeda, A quantitative LC–MS/MS method for determining ipragliflozin, a sodium-glucose co-transporter 2 (SGLT-2) inhibitor, and its application to a pharmacokinetic study in rats, J. Chromatogr. B. 1000 (2015) 22-28. doi:10.1016/j.jchromb.2015.07.013. [14] L. Chen, Y. Mao, D. Sharp, S. Schadt, S. Pagels, R. Press, T. Cheng, M. Potchoiba, W. Collins, Pharmacokinetics, Biotransformation, Distribution and Excretion of Empagliflozin, a Sodium-Glucose Co-Transporter (SGLT 2)

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Inhibitor, in Mice, Rats, and Dogs, J Pharm. Drug Devel. 3 (2015) 302. doi:10.15744/2348-9782.3.302. [15] M. Thevis, H. Geyer, W. Schänzer, Identification of oral antidiabetics and their metabolites in human urine by liquid chromatography/tandem mass spectrometry-a matter for doping control analysis, Rapid Commun. Mass Spectrom. 19 (2005) 928-936. doi:10.1002/rcm.1875. [16] A.R. Taylor, R.D. Brownsill, H. Grandon, F. Lefoulon, A. Petit, W. Luijten, P.G. Kopelman, B. Walther, Synthesis of putative metabolites and investigation of the metabolic fate of gliclazide, [1-(3-azabicyclo(3,3,0)oct-3-yl)-3-(4methylphenylsulfonyl) urea], in diabetic patients, Drug Metab Dispos. 24 (1996) 55-64. [17] Mass Spectrometry in the Clinical Laboratory: General Principles and Guidance; Approved Guideline. Clinical and Laboratory Standard Institute (CLSI) document C50-A. CLSI, Pennsylvania, USA, 2007. [18] Guide to Quality in Analytical Chemistry – An Aid to Accreditation. CITAC (The Cooperation on International Traceability in Analytical Chemistry) and EURACHEM (A Focus for Analytical Chemistry in Europe), 2002.

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Ying Hoo Lam: Methodology, Software, Data Curation, Validation, Investigation Mei Tik Leung: Writing – Original draft preparation Chor Kwan Ching: Writing – Review & Editing Tony Wing Lai Mak: Conceptualization, Supervision

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Alogliptin

Linagliptin

Saxagliptin

O

NH 2 N

H 2N

N

N

CF3

N N

N N

O

NH

N

NH2

N

O N

O

N

N

N

HO

N

N

Vildagliptin

N

O

O

N

Sitagliptin

OH

NH 2

O N

F

N

F F

Canagliflozin

Dapagliflozin OH

OH HO O

HO

OH O

HO

Ipragliflozin OH

HO

OH O

HO

Tofogliflozin

OH

OH

HO

OH

HO

Empagliflozin

OH O

HO

HO

OH O

HO O

Cl

F

Cl

S

O

S

O O

F

Glimepiride

Gliquidone

O

O

O

O

NH N

O

HN

O

HN

S

O

O

O

S

O

O

O

O

S

O

Tolazamide

HN

NH

Phenformin

Metformin NH 2

NH

O

O

S

O

S

NH 2

N

NH2

N

NH

O

O

NH2

N

N

HN

S

O

NH

NH2

O

S

Cl

Tolbutamide

O

NH

O

O

N

O

NH

NH

O

N

Chlorpropamide

N

HN

NH

O

Gliclazide

HN O

HN

O

N

Glibenclamide

HN

HN

HN

O S

Glipizide

NH

N

O

O

Cl

Pioglitazone O

Rosiglitazone H N

O

Nateglinide

O

O

O

S

OH

O

O

S

Acetohexamide (IS)

Repaglinide

H N

HN

HO O O

O

O

HN

NH

O

O

S

O

HN N

N

N N

O

Highlights:    

Urine drug testing is important in the work up of unexplained hypoglycemia Most published methods were not comprehensive and covered little metabolites A comprehensive LC-MS/MS method for antidiabetic drugs was developed and validated The established method was successfully applied in clinical toxicology service

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Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

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