The pathogen can be considered as the "receptor/target," whether in animals or humans. Appropriate animal models may therefore predict efficacy in humans by indicating optimum plasma/time profiles. Craig states that "animal models can describe the timecourse of in vivo antibiotic therapy and dose response relationships" . Such information could be aligned with findings from Phase 1 concerning attributes such as absorption, pharmacokinetics, protein binding, dose response,
Fig. 3.1 Effect of time above inhibitory concentration (T > MIC) of amoxicillin and kill rate for penicillin-resistant Streptomyces pneumonia. Reproduced with permission from
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metabolism, etc., to define a target plasma profile for dosage form design to deliver the requisite efficacy.
Craig and coworkers also propounded and validated the concept of "time above MIC" (T > MIC) as the performance standard for some antibiotics, showing that such time need not span the full dosage interval . Woodnut et al., using a rat infection model showed that inhibitory levels of the antibiotic amoxicillin against resistant S. pneumonia should exceed the MIC for about 35% of the dosing interval for optimal kill (Fig. 3.1 and ). This enabled the design of a prolonged release dosage form that delivered the requisite plasma profile and was clinically effective [10, 11].
Concepts such as T > MIC or "postantibiotic effect" may not apply to all novel anti infectives. Different mechanisms of action may decree otherwise. Nevertheless, it may be beneficial to evaluate the dynamics of activity in preclinical models. A dosage form, providing a plasma profile reflecting the findings could offer benefits such as better efficacy, reduced dose, and consequent reduced cost of goods in a therapeutic area where doses are traditionally high.
The aforementioned microbiological and formulation studies on amoxicillin were performed when it was a mature drug. In the light of today's knowledge, similar studies may be feasible during preclinical evaluation. Too often corporate policies mandate that Discovery Teams quickly pass on a drug candidate to Development groups so that their search for a followup candidate is not delayed. Discovery groups then try to eliminate (in followup compounds) deficiencies identified primarily by preclinical findings. This is high risk. In silico, in vitro, and other preclinical predictions of drug ADME properties remains an inexact science. At the same time, much expertise on the biology, molecular, or otherwise of a novel compound remains in Discovery. Feedback from Phase 1 or even later studies may suggest and warrant additional investigative work before further progression. Development groups may not be resourced for such work. Cooperative Discovery and Development operations, rather than silo cultures can greatly benefit the overall program.
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