In Vitro-In Vivo Correlations
Philip Burton, CEO and CSO of Admetrx (www.admetrx.com), presented a basic overview of ADMET and a case study addressing the need for in vitro data to have relevance in vivo. Discussion of in vitro-in vivo correlations stressed the value and limitations of the data.
The FDA Critical Path Initiative, published in 2004, states that in 2000, 8% of compounds passed the clinical trial process, as opposed to 14% historically. “We generate more data, certainly,” Burton noted, “but I believe that in the process of advancing candidates, we have thrown out a lot of good compounds. The number of candidates submitted for trial is keeping pace with spending, but a smaller percentage of these survive late-stage development. Overall, productivity is declining.”
The challenge is not to advance more candidates, but to advance the best of them, “and I don’t think that is what is happening,” said Burton. “A better understanding of the data is needed and the decision-making process needs to be improved. We need better in vitro toxicity tools. We need better data-integration tools, recognizing it is the composite profile of a molecule that dictates its success rather than any individual property. The industry is waiting for the development of these tools.”
And some of these advances will have immediate impact. “Better prediction of safety in larger populations, better understanding of drug-drug interactions, and a better understanding of efficacy are the tools needed to accomplish these things, and as they come on line the drug discovery process will improve,” said Burton. “But the process takes so long to begin with that you may not see the results for a couple of years after these tools are introduced.”
McKim noted that there are multiple parameters that both biologists and chemists need to track. “A chemist needs to have the ability to evaluate whether increasing the potency of a compound also increases the toxicity,” McKim said. “In addition, in vitro biochemical assays can provide important information on subcellular targets and potential mechanisms of toxicity long before the compound even enters an animal study.
“And if you don’t have a rapid screening system with an in vivo correlate (cell-animal bridge) that allows the ability to track new drug attributes as well as toxicity, you will have a hard time knowing whether the compound is going to be successful prior to the animal safety studies.”
McKim said that regardless of the methodology used to collect in vitro data, the key to using the information is to link changes observed in the cell models to effects in the animal model. He uses an algorithm that analyzes multiple endpoints over a broad exposure range to provide a predictive value for toxicity in animals. “This is where cytotoxicity programs have failed in the past.
“We’re focused now on trying to identify biochemical profiles associated with unexpected toxicity of approved drugs in small patient populations. There have been a number of noteworthy drugs that have passed clinical trials, only to be pulled from the market because of severe toxic effects in patients.” In the future, McKim said, “we will see those red flags sooner.”
The future will also focus on speed, efficiency, and reducing animal usage. Developing more robust data sets early so that better decisions for compound advancement can be made is the goal. And that, McKim noted, will depend on how drug discovery is approached.
“It is not enough to look at any one parameter—you can’t just look at efficacy, solubility, or ADME. You also need to look at toxicity and the intended therapeutic use to understand whether or not the compound in question has a tolerable risk profile. All of these things need to go into the decision-making process.”
The blood-brain barrier, which provides protection for the sensitive neural microenvironment, also creates a challenge for medicinal chemists, said Steven Hitchcock, director of medicinal chemistry at Amgen (www.amgen.com).