The terms describing several types of early clinical studies are given below.

- Treatment Mechanism
- Early developmental trial that investigates mechanism of treatment effect, e.g., a pharmacokinetics study of absorption and elimination of the drug from the human body

- Phase I
- Imprecise term for dose-ranging studies

- Dose-escalation
- Design or component of a design that specifies methods for increases in dose for subsequent subjects

- Dose-ranging
- Design that tests some or all of a prespecified set of doses (fixed design points)

- Dose-finding
- Design that titrates dose to a prespecified optimum based on biological or clinical considerations

Definitions from Piantodosi (2005)

**Dose-finding (DF) trials** are Phase I studies with the objective of determining the optimal biological dose (OBD) of a drug. In order to determine the dose with the highest potential for efficacy in the patient population that still meets safety criteria, dose-finding studies are typically conducted by administering *sequentially rising doses* to successive groups of individuals. Such studies may be conducted in healthy volunteers or in patients with the disease.

A question the investigator must answer in designing a dose-finding study is how to characterize an optimum dose. Should the optimum dose be selected on the basis of the highest therapeutic index (the maximal separation between risk and benefit)? Or is the optimal dose the level that maximizes therapeutic benefit while maintaining risk below a predetermined threshold? What measures will denote risk and benefit?

An optimal dose can be selected on the basis of efficacy alone, such as when a minimum effective dose (MED) is chosen for a pain-relieving medication and defined as the dose which eliminates mild-to-moderate pain in 80% of trial participants. In another case, the optimal dose might be selected as the highest dose that is associated with serious side effects in no more than 1 of 20 patients. This would be a maximum nontoxic dose (MND). In cancer therapeutics, the optimal dose for a cytotoxic drug designed to shrink tumors could be defined as the level that yields serious but reversible toxicity in no more than 30% of the patients. This is a maximum tolerated dose (MTD). Care in defining the conditions for optimality is critical to a dose-finding study.

Most DF trials are sequential studies such that the number of subjects is itself an outcome of the trial. Convincing evidence characterizing the relationship between dose and safety can be obtained after studying a small set of patients. Hence sample size is not a major concern DF trials.

An idealized DF study would be similar to an animal bioassay design, with K fixed doses at increasing levels, d_{1}, d_{2}, ... , d_{K}. The hypothesized optimal dose would lie between d_{1} and d_{K}. The n participants would be randomized to each of the K dose groups and the binary response of toxicity would be noted for each participant. A mathematical model could then be fit to the proportional responses over the doses such that the optimal dose could be determined.

Would you agree to participate in such a study? Think carefully ...

Most likely, your answer is no because you would not want to risk being assigned to the highest dose level of this unproven drug as your first treatment. There is a principle here: it is unethical to treat humans at high doses of a drug without any prior knowledge of their responses at lower levels. Furthermore, ethics compel a design that minimizes the number of patients treated with both low ineffective doses and high toxic doses.

Thus, along with defining optimality, a DF study design usually includes a method for determining the starting dose for the patient, specification of dose increments and cohort sizes, definition of dose-limiting toxicities as well as the decision rules for escalation and de-escalation of the dose.

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Continual Reassessment Method
Section* *

The **continual reassessment method** (CRM) allows fitting a mathematical model to observed data during the study from which it estimates an optimal dose via extrapolation or interpolation. The next cohort of patients is assigned to the estimated optimal dose. A study using CRM would **not** have an a priori defined set of doses; thus is dose-finding study. The CRM itself can be thought of an algorithm for updating the best guess regarding the optimal dose. Bayesian approaches have also been incorporated into the CRM and the method is applicable for many types of responses.

In contrast to a dose*-finding* study, a dose-*ranging* study uses pre-specified design points.

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Fibonacci Dose-Ranging Designs
Section* *

Fibonacci, a thirteenth-century Italian mathematician, popularized the number sequence 1, 1, 2, 3, 5, 8, 13, 21, 34 ... (a number in the sequence is the sum of the two previous numbers).

A fixed dosing scheme can be based on the Fibonacci sequence. For example, the first cohort of n participants is assigned dose D, the initial dose. If they tolerate this dose D well, the next cohort of n participants is assigned dose 2D. If all goes well with the second cohort, then a third cohort is assigned dose 3D, the fourth cohort is assigned does 5D, etc. The process is discontinued when one of the cohorts exhibits toxicity. Numerous modifications have been proposed to the Fibonacci scheme, such as allowing for de-escalation as well as escalation.