Letter to the editor

Which concentrations are optimal for in vitro testing?

Wiebke Albrecht1[*]

1Leibniz Research Centre for Working Environment and Human Factors, Ardeystr. 67, 44139 Dortmund, Germany

EXCLI J 2020;19:Doc1172


Dear Editor,

Currently, many research activities in the field of in vitro models focus at predicting human organ toxicity, e.g. of the liver (Gomez-Lechon et al., 2014[4]; Grinberg et al., 2014[6], 2018[5]; Frey et al., 2014[3]), kidney (Li et al., 2013[12], 2014[11]; Sjögren et al., 2018[15]; Sjögren and Hornberg, 2019[16]), heart (Nemade et al., 2018[13]; Chaudhari et al., 2018[2]) or developmental toxicity (Krug et al., 2013[9]; Waldmann et al., 2014[17]; Shinde et al., 2017[14]). All studies face a similar challenge, which is the choice of concentrations for in vitro testing (Leist et al., 2017[10]). This question has recently been discussed in an editorial of the Archives of Toxicology, where the authors pointed out that in vitro tests are usually performed at a concentration range around and above the plasma peak concentrations (Cmax) of a drug in humans (Hengstler et al., 2020[8]). A typical strategy is to test relatively high concentrations, often 20- or even 200-fold higher than the human plasma Cmax. The choice of high concentrations was justified by the observation that usually higher concentrations are required in the culture medium to induce cell damage compared to the Cmax that is known to cause adverse effects in vivo. We made a similar observation in a recent study using human hepatocytes (Albrecht et al., 2019[1]; Gu et al., 2018[7]). The factor by which in vitro concentrations have to be higher than the corresponding in vivo plasma concentration in order to cause similar biological effects in the target cells is the in vitro-in vivo scaling factor.

However, it should be considered that it is not yet clear if all compounds require identical in vitro-in vivo scaling factors. It cannot be excluded that e.g. compounds, whose toxicity depends on specific metabolic pathways may require higher scaling factors than compounds that do not require bio-activation. Moreover, scaling may also depend on the mechanism of toxicity (Hengstler et al., 2020[8]). To gain more insight into the requirements of optimal scaling it is not helpful to test only one or two concentrations, e.g. 20- and/or 200-fold the Cmax and on this basis decide if a compound is positive or negative in the in vitro assay. Rather a concentration-dependent test with not too high dilution factors, such as 2- or at most 3.16-fold is helpful to be able to precisely determine the concentration when toxic effects occur, expressed e.g. as EC10 or EC50. This is a precondition to be able to elucidate if groups of compounds categorized e.g. by metabolic activation or mechanism of action require different scaling factors. A limitation to be overcome in the future is that too few studies established high quality, reproducible concentration response relationships for sufficiently high numbers of test compounds that allow a systematic comparison to the human in vivo situation.

Conflict of interest

The author declares no conflict of interest.



1. Albrecht W, Kappenberg F, Brecklinghaus T, Stoeber R, Marchan R, Zhang M, et al. Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations. Arch Toxicol. 2019;93:1609-37. doi: 10.1007/s00204-019-02492-9
2. Chaudhari U, Nemade H, Sureshkumar P, Vinken M, Ates G, Rogiers V, et al. Functional cardiotoxicity assessment of cosmetic compounds using human-induced pluripotent stem cell-derived cardiomyocytes. Arch Toxicol. 2018;92:371-81. doi: 10.1007/s00204-017-2065-z
3. Frey O, Misun PM, Fluri DA, Hengstler JG, Hierlemann A. Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis. Nat Commun. 2014;5:4250. doi: 10.1038/ncomms5250
4. Gomez-Lechon MJ, Tolosa L, Conde I, Donato MT. Competency of different cell models to predict human hepatotoxic drugs. Expert Opin Drug Metab Toxicol. 2014;10:1553–68. doi: 10.1517/17425255.2014.967680
5. Grinberg M, Stöber RM, Albrecht W, Edlund K, Schug M, Godoy P, et al. Toxicogenomics directory of rat hepatotoxicants in vivo and in cultivated hepatocytes. Arch Toxicol. 2018;92:3517-33. doi: 10.1007/s00204-018-2352-3
6. Grinberg M, Stöber RM, Edlund K, Rempel E, Godoy P, Reif R, et al. Toxicogenomics directory of chemically exposed human hepatocytes. Arch Toxicol. 2014;88:2261-87. doi: 10.1007/s00204-014-1400-x
7. Gu X, Albrecht W, Edlund K, Kappenberg F, Rahnenführer J, Leist M, et al. Relevance of the incubation period in cytotoxicity testing with primary human hepatocytes. Arch Toxicol. 2018;92:3505-15. doi: 10.1007/s00204-018-2302-0
8. Hengstler JG, Sjögren AK, Zink D, Hornberg JJ. In vitro prediction of organ toxicity: the challenges of scaling and secondary mechanisms of toxicity. Arch Toxicol. 2020;94:353-6. doi: 10.1007/s00204-020-02669-7
9. Krug AK, Kolde R, Gaspar JA, Rempel E, Balmer NV, Meganathan K, et al. Human embryonic stem cell-derived test systems for developmental neurotoxicity: a transcriptomics approach. Arch Toxicol. 2013;87:123-43. doi: 10.1007/s00204-012-0967-3
10. Leist M, Ghallab A, Graepel R, Marchan R, Hassan R, Bennekou SH, et al. Adverse outcome pathways: opportunities, limitations and open questions. Arch Toxicol. 2017;91:3477-505. doi: 10.1007/s00204-017-2045-3
11. Li Y, Kandasamy K, Chuah JK, Lam YN, Toh WS, Oo ZY, et al. Identification of nephrotoxic compounds with embryonic stem-cell-derived human renal proximal tubular-like cells. Mol Pharm. 2014;11:1982–90. doi: https://doi.org/10.1021/mp400637s
12. Li Y, Oo ZY, Chang SY, Huang P, Eng KG, Zeng JL, et al. An in vitro method for the prediction of renal proximal tubular toxicity in humans. Toxicol Res. 2013;2:352–62. doi: https://doi.org/10.1039/c3tx50042j
13. Nemade H, Chaudhari U, Acharya A, Hescheler J, Hengstler JG, Papadopoulos S, et al. Cell death mechanisms of the anti-cancer drug etoposide on human cardiomyocytes isolated from pluripotent stem cells. Arch Toxicol. 2018;92:1507-24. doi: 10.1007/s00204-018-2170-7
14. Shinde V, Hoelting L, Srinivasan SP, Meisig J, Meganathan K, Jagtap S, et al. Definition of transcriptome-based indices for quantitative characterization of chemically disturbed stem cell development: introduction of the STOP-Toxukn and STOP-Toxukk tests. Arch Toxicol. 2017;91:839-64. doi: 10.1007/s00204-016-1741-8
15. Sjögren AK, Breitholtz K, Ahlberg E, Milton L, Forsgard M, Persson M, et al. A novel multi-parametric high content screening assay in ciPTEC-OAT1 to predict drug-induced nephrotoxicity during drug discovery. Arch Toxicol. 2018;92:3175–90. doi: https://doi.org/10.1007/s00204-018-2284-y
16. Sjögren AK, Hornberg JJ. Compound selection and annotation to validate the predictivity of in vitro toxicity assays for use in drug discovery, in response to Commentary by Dr. Zink (Zink D. Arch Toxicol (2019)). Arch Toxicol. 2019;93:225–6. doi: https://doi.org/10.1007/s00204-018-2359-9
17. Waldmann T, Rempel E, Balmer NV, König A, Kolde R, Gaspar JA, et al. Design principles of concentration-dependent transcriptome deviations in drug-exposed differentiating stem cells. Chem Res Toxicol. 2014;27:408-20. doi: 10.1021/tx400402j

[*] Corresponding Author:

Wiebke Albrecht, Leibniz Research Centre for Working Environment and Human Factors, Ardeystr. 67, 44139 Dortmund, Germany, eMail: albrecht@ifado.de