Calculadora de semivida

Introduce la semivida de un fármaco para ver cómo disminuyen las concentraciones plasmáticas con el tiempo según la cinética de primer orden. La herramienta calcula la fracción restante y el porcentaje eliminado en cada intervalo de semivida, además del tiempo necesario para alcanzar el estado estacionario (5 semividas, ~97% del estado estacionario).

Half-Life (hours)

Number of Half-Lives

Half-Life

Time to Steady State (5 × t½)

Total Timeline

Half-Lives	Time (h)	Remaining (%)	Eliminated (%)

What is Drug Half-Life?

The elimination half-life (t½) is the time required for the plasma concentration of a drug to decrease by 50%. Most drugs follow first-order elimination kinetics, meaning a constant fraction — not a constant amount — is eliminated per unit time. This produces the exponential decay curve seen in pharmacokinetic profiles and makes t½ a stable, dose-independent parameter under linear conditions.

A critical clinical principle is that approximately 97% of a drug is eliminated after five consecutive half-lives, which is why five half-lives is used as the practical threshold for declaring a drug "cleared" from the body. This rule applies symmetrically: five half-lives is also the time needed to reach 97% of steady-state plasma concentrations during repeated dosing. Drugs with short half-lives (e.g., ibuprofen ~2h) require frequent dosing to maintain therapeutic concentrations, while drugs with long half-lives (e.g., amiodarone 40–55 days) accumulate gradually and persist long after discontinuation.

Factors that influence drug half-life include hepatic metabolism (CYP450 enzyme activity, first-pass effect), renal clearance, volume of distribution, and plasma protein binding. Liver disease, kidney impairment, and drug interactions that inhibit metabolizing enzymes can significantly extend half-life, increasing accumulation risk. Conversely, enzyme inducers like rifampin can shorten half-life substantially, reducing therapeutic efficacy.

Aviso médico

This content is for educational and informational purposes only. It is not a substitute for professional medical advice, diagnosis, or treatment. Always consult a qualified healthcare provider before making medication decisions.

Data sources: ChEMBL, PubChem, DailyMed.

How to Use

1
Enter drug concentration data or select a drug
Input plasma concentration values at two or more time points after a dose (in ng/mL or µg/mL) along with the corresponding time points in hours, or select a drug from the database to use published pharmacokinetic parameters from FDA-reviewed clinical pharmacology studies.
2
Calculate elimination half-life
The calculator applies the first-order elimination kinetics equation t½ = 0.693 / k_el, where k_el is the elimination rate constant derived by linear regression of the log-linear terminal phase of the concentration-time curve. For multi-compartment drugs, only the terminal elimination phase is used for t½ calculation.
3
Interpret clinical dosing implications
Use the calculated half-life to estimate time to steady state (approximately 4–5 half-lives), duration of drug action after stopping therapy, and appropriate dosing interval. The tool flags considerations for drugs with non-linear pharmacokinetics where first-order half-life estimates have limited predictive value.

About

Elimination half-life is one of the most clinically useful pharmacokinetic parameters, governing dosing interval selection, washout timing, and the interpretation of plasma drug level monitoring. Under first-order kinetics, where a constant fraction of drug is eliminated per unit time, the relationship between half-life, volume of distribution, and clearance is mathematically defined, enabling rational prediction of drug accumulation, time to steady state, and time to drug removal after discontinuation. These calculations underpin clinical decisions ranging from antibiotic dosing optimization using PK/PD targets to pre-procedural discontinuation of anticoagulants.

FDA clinical pharmacology guidance (M10 Bioanalytical Method Validation, CPG pharmacokinetic study design) establishes the methodological standards for measuring half-life in drug development, including specifications for sampling frequency, analytical sensitivity, and regression methods for calculating the terminal elimination rate constant. Non-compartmental analysis (NCA) using software such as Phoenix WinNonlin or R packages is the regulatory standard for calculating primary pharmacokinetic parameters from concentration-time profiles. Compartmental modeling is used when mechanistic understanding of drug distribution and elimination is needed or when sparse data requires population pharmacokinetic (PopPK) approaches.

In clinical practice, understanding a drug's half-life enables pharmacists to counsel patients on dosing adherence implications (missing a dose of a long-half-life drug has less immediate impact than missing a short-half-life drug) and to interpret potentially toxic plasma drug levels in the context of the time elapsed since the last dose. This calculator provides accessible application of standard pharmacokinetic equations, drawing on published FDA clinical pharmacology parameters where available, to support pharmaceutical education and informed clinical conversations.

FAQ

What is elimination half-life and why does it matter?

Elimination half-life (t½) is the time required for the plasma concentration of a drug to decrease by 50% under first-order elimination kinetics. It determines dosing interval (drugs are typically dosed at intervals of 0.5 to 2 half-lives for sustained therapeutic coverage), time to steady state (4–5 half-lives to reach 90–97% of steady-state concentration with fixed dosing), and washout time after discontinuation. Drugs with long half-lives such as amiodarone (40–55 days) require weeks to reach steady state and weeks to wash out, while drugs with short half-lives such as morphine (2–4 hours) require more frequent dosing or sustained-release formulations.

How does volume of distribution affect half-life?

Elimination half-life is related to both volume of distribution (Vd) and clearance (CL) by the equation t½ = (0.693 × Vd) / CL. Drugs with large volumes of distribution, indicating extensive tissue binding or lipophilicity, have longer half-lives even if hepatic clearance is high, because a large fraction of drug is sequestered outside the vascular compartment and not immediately available for elimination. Chloroquine, for example, has a volume of distribution of several hundred liters per kilogram and a half-life measured in weeks despite extensive hepatic metabolism.

What are multi-compartment pharmacokinetics?

Many drugs follow multi-compartment pharmacokinetics where plasma concentration declines in multiple phases after administration: an initial distribution phase as drug moves from plasma to tissues, followed by a slower elimination phase reflecting systemic clearance. For two-compartment drugs, two half-lives can be calculated: a distribution half-life (alpha t½) and an elimination half-life (beta t½). Clinical dosing and drug interaction assessments typically focus on the terminal elimination half-life, but for highly lipophilic drugs such as benzodiazepines and certain antiarrhythmics, the distribution phase contributes meaningfully to early drug action and offset.

Which diseases alter drug half-life?

Hepatic impairment reduces the clearance of drugs metabolized by CYP450 enzymes, extending half-life and increasing the risk of drug accumulation. FDA guidance on pharmacokinetics in hepatic impairment (CPG7303.12) recommends dedicated clinical studies for drugs substantially cleared by the liver. Renal impairment reduces renal drug elimination and also affects active metabolite clearance, potentially requiring dose adjustment even for parent drugs that are hepatically cleared if active metabolites are renally excreted. Hypothyroidism reduces CYP enzyme activity, and thyroid replacement therapy can alter the pharmacokinetics of co-administered drugs such as warfarin.

How does non-linear pharmacokinetics affect half-life calculations?

Non-linear (saturable, Michaelis-Menten) pharmacokinetics occur when elimination processes become saturated at therapeutic drug concentrations, causing clearance to decrease and apparent half-life to increase with rising dose. Phenytoin is the classic example: at low doses its metabolism follows first-order kinetics with a predictable half-life, but as doses approach saturation of CYP2C9, small dose increases produce disproportionately large plasma concentration increases. Ethanol and aspirin at high doses also exhibit saturable kinetics. Standard t½ calculation assumes first-order kinetics and is unreliable for drugs with documented non-linear pharmacokinetics; phenytoin requires Michaelis-Menten parameter-based dosing calculations instead.