L: Antineoplastic and immunomodulating agents

ATC group L for modelers: the level 2 map with example drugs, and the antineoplastic modeling notes held at L01.
Modified

September 21, 2026

Agents used to kill malignant cells and to push the immune system either way, from cytotoxics through targeted small molecules to antibodies and cell products. The endpoint that decides the program, survival, reads out late and is linked to exposure only through intermediates such as tumor size [1].

On 27 August 1942 a Yale team under Louis Goodman and Alfred Gilman gave intravenous nitrogen mustard, a chemical warfare agent, to a factory worker with lymphosarcoma. Ten daily doses left no tumor on biopsy, though it returned by day 49 [2].

Table 1: ATC L level 2 codes
Level 2 code Description In plain terms Example drug
L01 Antineoplastic agents drugs that kill or block tumor cells Pembrolizumab (L01FF02) / trastuzumab (L01FD01)
L02 Endocrine therapy hormone-blocking therapy, mainly breast and prostate cancer Tamoxifen (L02BA01) / anastrozole (L02BG03)
L03 Immunostimulants Filgrastim (L03AA02) / pegfilgrastim (L03AA13)
L04 Immunosuppressants Tacrolimus (L04AD02) / adalimumab (L04AB04)

Modeling notes

Mechanistic extrapolation. PBPK is routine for kinase inhibitors, predicting CYP3A and gastric-pH interactions that reach labels; QSP extrapolates immuno-oncology dosing, notably CD3 bispecific T-cell engagers, from preclinical data [3,4].

E-R Exposure-response for targeted agents is drug-specific, not class-wide: no efficacy relationship was detectable across the osimertinib dose range [5], while trough concentrations separated progression-free survival for crizotinib and alectinib [6].

References

[1]
Bender BC, Schindler E, Friberg LE. Population pharmacokinetic-pharmacodynamic modelling in oncology: A tool for predicting clinical response. British Journal of Clinical Pharmacology 2015;79:56–71. https://doi.org/10.1111/bcp.12258.
[2]
Christakis P. The birth of chemotherapy at Yale. Bicentennial lecture series: Surgery Grand Round. The Yale Journal of Biology and Medicine 2011;84:169–72.
[3]
Yoshida K, Budha N, Jin JY. Impact of Physiologically Based Pharmacokinetic Models on Regulatory Reviews and Product Labels: Frequent Utilization in the Field of Oncology. Clinical Pharmacology & Therapeutics 2017;101:597–602. https://doi.org/10.1002/cpt.622.
[4]
Betts A, Haddish-Berhane N, Shah DK, van der Graaf PH, Barletta F, King L, et al. A Translational Quantitative Systems Pharmacology Model for CD3 Bispecific Molecules: Application to Quantify T Cell-Mediated Tumor Cell Killing by P-Cadherin LP DART. The AAPS Journal 2019;21:66. https://doi.org/10.1208/s12248-019-0332-z.
[5]
Brown K, Comisar C, Witjes H, Maringwa J, Greef R de, Vishwanathan K, et al. Population pharmacokinetics and exposure-response of osimertinib in patients with non-small cell lung cancer. British Journal of Clinical Pharmacology 2017. https://doi.org/10.1111/bcp.13223.
[6]
Groenland SL, Geel DR, Janssen JM, Vries N de, Rosing H, Beijnen JH, et al. Exposure-response analyses of anaplastic lymphoma kinase inhibitors crizotinib and alectinib in non-small cell lung cancer patients. Clinical Pharmacology & Therapeutics 2021. https://doi.org/10.1002/cpt.1989.