Aminoglycosides are a class of molecules that are used for the treatment of serious gram-negative systemic infections. Some common aminoglycosides are tobramycin, gentamicin, amikacin, and neomycin. Aminoglycosides have bactericidal activity against most gram-negative bacteria including Acinetobacter, Citrobacter, Enterobacter, E. Coli, Klebsiella, Proteus, Providencia, Pseudomanas, Salmonella, Serratia and Shigella. Aminoglycosides are also active against most strains of Staphylococcus aureus and S. epidermidis. Most strains of enterococcus are resistant to aminoglycosides alone, however when used in combination with penicillins they are often effective in enterococcal endocarditis due to synergistic antimicrobial mechanisms. Anaerobic bacteria are universally resistant because aminoglycoside transport into cells is oxygen-dependent.
The major disadvantage of the aminoglycosides is their association with nephrotoxicity and ototoxicity, both of which are associated with elevated trough levels and sustained elevated peak levels. Aminoglycoside nephrotoxicity manifests clinically as nonoliguric renal failure, with a slow rise in serum creatinine and a hypoosmolar urinary output developing after several days of therapy. The reported incidence of nephrotoxicity averages 6% to 10%. Nephrotoxicity rates do not vary significantly among the different aminoglycosides. Factors associated with nephrotoxicity include duration of treatment, increasing age, compromised renal function, volume depletion, elevated peak and trough levels, concurrent nephrotoxic drugs (i.e., vancomycin) and previous exposure to aminoglycosides. Aminoglycosides can cause permanent vestibular and/or auditory ototoxicity. Overt otoxicity occurs in 2% to 10% of patients treated with aminoglycosides. Factors associated with otoxicity include increasing age, duration of therapy, elevated peak and trough levels, concurrent loop diuretics or vancomycin, underlying disease states and previous exposure to aminoglycosides.
The efficacy and toxicity of aminoglycosides are directly related to the peak circulating levels of the drug. Therefore, administration of aminoglycosides requires a balancing act between providing enough drug to kill the bacteria and too much drug that might cause renal or otic toxicity. Efficacy is normally achieved when peak concentrations of the aminoglycoside reach 8-10 times the minimum inhibitory concentration (MIC). For gentamicin and tobramycin the risk of ototoxicity and nephrotoxicity is increased if peak levels are consistently maintained above 12 to 14 mcg/ml or trough levels consistently exceed 2 mcg/ml. For amikacin, peak levels above 32 to 34 mcg/ml or trough levels greater than 10 mcg/ml have been associated with a higher risk of ototoxicity and nephrotoxicity.
To manage the balancing act between efficacy and toxicity, the pharmacokinetics of aminoglycosides must be understood and used to accurately predict plasma concentrations in the patient. Aminoglycosides have limited tissue distribution, and are cleared by the kidney. Thus knowledge about the body weight, tissue composition, and kidney function are critical to permitting proper dosing of aminoglycosides. The pharmacokinetics of aminoglycosides depend on many physiologic and demographic factors (e.g. age, weight, BMI, kidney function, gender, etc.), therefore those factors must be collected and input into an appropriate model to predict the exposure to an aminoglycoside regimen before administration. Aminoglycosides are an example in which pharmacokinetics can be used to customize a patient’s treatment plan to ensure efficacy and minimize toxicity.
At least two million people become infected with treatment-resistant bacteria each year in the US alone. At least 23,000 die as a direct result; many more lose their lives to other conditions complicated by the infections. With antibiotic resistance on the rise and a low rate of approvals for new antibiotics, there is urgent need to make new treatment options available to patients quickly, efficiently, and safely. Read this case study to learn how model-based analyses were used to support confident go/no go decisions, to improve understanding of drug exposure in diverse populations, and to anticipate and address regulatory needs for the drug’s expedited review and approval.