J: Antiinfectives for systemic use

ATC group J for modelers: potency as a property of the pathogen isolate, with antibacterial and antiviral notes held at J01 and J05.
Modified

September 22, 2026

Drugs given systemically against an invading organism, bacteria, fungi, mycobacteria and viruses, plus immune sera and vaccines under the same letter [1]. The potency term is a property of the pathogen isolate, its MIC, rather than of the patient (see PKPD) [2].

Fleming’s mould plate of 1928 became a medicine only in February 1941, when Florey’s Oxford group treated a constable, Albert Alexander [3,4]. He responded, but penicillin re-purified from his urine was not enough to keep the course going, the supply ran out and he died [3,5]. Fleming, Florey and Chain shared the 1945 Nobel Prize [5].

Table 1: ATC J level 2 codes
Level 2 code Description In plain terms Example drug
J01 Antibacterials for systemic use Amoxicillin (J01CA04) / ceftriaxone (J01DD04)
J02 Antimycotics for systemic use antifungals taken into the bloodstream Fluconazole (J02AC01) / caspofungin (J02AX04)
J04 Antimycobacterials drugs against tuberculosis and leprosy Rifampicin (J04AB02) / isoniazid (J04AC01)
J05 Antivirals for systemic use Dolutegravir (J05AJ03) / sofosbuvir (J05AP08)
J06 Immune sera and immunoglobulins ready-made antibodies given as instant protection Normal human immunoglobulin for intravascular administration (J06BA02) / nirsevimab (J06BD08)
J07 Vaccines Influenza, inactivated, split virus or surface antigen (J07BB02) / covid-19, RNA-based vaccine (J07BN01)

Modeling notes

Endpoint. For antibacterials it is bacterial count, log CFU, from time-kill or animal infection experiments [6,7]. For J05 it is plasma viral load [8,9].

Easy to overlook. MIC is a discrete two-fold scale carrying real measurement error [10]. Unbound concentration is the active one, yet there is no standard way to account for protein binding in in vitro pharmacodynamic testing [11]. After hepatitis A vaccination, antibody titres decay multiphasically, set by the lifespans of antibody and of short- and long-lived plasma cells [12].

Mechanistic extrapolation. PBPK has been applied to antiretrovirals where trials are hard: exposure in pregnancy [13] and release from long-acting intramuscular depots [14]. For J04 the hollow fiber system is qualified by the EMA as a methodology supporting the development of antituberculosis regimens [15].

References

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WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD index 2026 2026.
[2]
Mouton JW, Dudley MN, Cars O, Derendorf H, Drusano GL. Standardization of pharmacokinetic/pharmacodynamic (PK/PD) terminology for anti-infective drugs: An update. J Antimicrob Chemother 2005;55:601–7. https://doi.org/10.1093/jac/dki079.
[3]
Sheppard D. Short-course antibiotic therapy: The next frontier in antimicrobial stewardship. Canada Communicable Disease Report 2022;48:496–501. https://doi.org/10.14745/ccdr.v48i1112a01.
[4]
Barrett MP. The legacy of penicillin’s first patient. Pharmacol Res 2023;192:106772. https://doi.org/10.1016/j.phrs.2023.106772.
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Gaynes R. The discovery of penicillin: New insights after more than 75 years of clinical use. Emerg Infect Dis 2017;23:849–53. https://doi.org/10.3201/eid2305.161556.
[6]
Craig WA. Pharmacokinetic/pharmacodynamic parameters: Rationale for antibacterial dosing of mice and men. Clin Infect Dis 1998;26:1–10. https://doi.org/10.1086/516284.
[7]
Nielsen EI, Viberg A, Löwdin E, Cars O, Karlsson MO, Sandström M. Semimechanistic pharmacokinetic/pharmacodynamic model for assessment of activity of antibacterial agents from time-kill curve experiments. Antimicrob Agents Chemother 2007;51:128–36. https://doi.org/10.1128/aac.00604-06.
[8]
Perelson AS, Neumann AU, Markowitz M, Leonard JM, Ho DD. HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time. Science 1996;271:1582–6. https://doi.org/10.1126/science.271.5255.1582.
[9]
Neumann AU, Lam NP, Dahari H, Gretch DR, Wiley TE, Layden TJ, et al. Hepatitis C viral dynamics in vivo and the antiviral efficacy of interferon-\(\alpha\) therapy. Science 1998;282:103–7. https://doi.org/10.1126/science.282.5386.103.
[10]
Mouton JW, Meletiadis J, Voss A, Turnidge J. Variation of MIC measurements: The contribution of strain and laboratory variability to measurement precision. J Antimicrob Chemother 2018;73:2374–9. https://doi.org/10.1093/jac/dky232.
[11]
Zeitlinger MA, Derendorf H, Mouton JW, Cars O, Craig WA, Andes D, et al. Protein binding: Do we ever learn? Antimicrob Agents Chemother 2011;55:3067–74. https://doi.org/10.1128/AAC.01433-10.
[12]
Andraud M, Lejeune O, Musoro JZ, Ogunjimi B, Beutels P, Hens N. Living on three time scales: The dynamics of plasma cell and antibody populations illustrated for hepatitis A virus. PLoS Comput Biol 2012;8:e1002418. https://doi.org/10.1371/journal.pcbi.1002418.
[13]
De Sousa Mendes M, Hirt D, Urien S, Valade E, Bouazza N, Foissac F, et al. Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women. Br J Clin Pharmacol 2015;80:1031–41. https://doi.org/10.1111/bcp.12685.
[14]
Bettonte S, Berton M, Battegay M, Stader F, Marzolini C. Development of a physiologically-based pharmacokinetic model to simulate the pharmacokinetics of intramuscular antiretroviral drugs. CPT Pharmacometrics Syst Pharmacol 2024;13:781–94. https://doi.org/10.1002/psp4.13118.
[15]
Cavaleri M, Manolis E. Hollow fiber system model for tuberculosis: The European Medicines Agency experience. Clin Infect Dis 2015;61:S1–4. https://doi.org/10.1093/cid/civ484.