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Modeling and Simulation , Data Sciences

How to leverage Modeling and Simulation in the candidate development stage to help ensure clinical success

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All drug developers wish they had a crystal ball that could predict the future outcome of their molecules. Having the ability to know whether you have clinical or commercial success before investing the time and money required would be a game changer. 

Unfortunately, magic and mystics do not have the proven and peer-reviewed data needed to make clinical decisions. Fortunately, Modeling and Simulation (M&S) provides another way to predict the clinical performance of a molecule, based on a much more robust and holistic approach.

M&S is a proven scientific approach used to inform key drug development decisions, and it can be employed throughout the development lifecycle of a drug. Specifically, physiologically based pharmacokinetic (PBPK) modeling integrates knowledge of a drug’s characteristics (measured or in-silico properties) with physiological information, allowing for maximum leverage from data already obtained. Drug developers can use this approach early in the candidate development stage to help guide their formulation strategy and ensure that their program is well prepared for entering the clinical phase.

We employ M&S during candidate development, where measured data on lead candidates can be sparse. 

Our M&S team can use this limited dataset to enable an initial understanding of a client’s molecule and how it may behave in humans. In the first instance, this may be simply a prediction of the fraction absorbed or a Developability Classification System (DCS) assessment, which can be made solely from physicochemical properties, such as solubility, logP, pKa, and permeability. If measured data for any of these parameters is not available, we can easily predict these properties from the chemical structure using the GastroPlus® software “ADMET Predictor”, which contains quantitative structure–activity relationship (QSPR) models for many properties, such as human effective permeability (Peff) and logP among others. By obtaining this key information early, we ensure our customers are prepared and can identify a formulation strategy well before moving into the clinical phase.

What is a DCS assessment?

We typically conduct a DCS assessment following (or just prior to) candidate selection, which helps to inform molecule developability and the formulation strategy. We utilize biorelevant solubility data (in fasted-state simulated intestinal fluid) and permeability information (predicted from either in-vitro or in-silico data using GastroPlus ADMET Predictor) along with the expected therapeutic dose to classify our client’s molecule. This classification informs early in the development process whether simple techniques, like micronization, are likely to be appropriate for our client’s molecule or whether more sophisticated technologies will be required.

How is fraction absorbed predicted?

At Quotient Sciences, we use the PBPK modeling software GastroPlus to predict the dissolution and absorption of a compound in the gastrointestinal (GI) tract. This software mechanistically predicts the behavior of a drug, considering the physicochemical properties of the molecule (e.g. ionization status, solubility, and lipophilicity) and the changing environment of the GI tract (e.g. pH, volume, surface area, and bile salt concentrations). Fraction absorbed can be predicted across a dose range and for different scenarios, such as with and without food or in the presence of acid-reducing agents like proton pump inhibitors. Knowing how much (and where) a drug is likely to be absorbed in different scenarios can help to inform the formulation strategy for the clinical phase.

Can PBPK modeling also be used to predict first-in-human (FIH) performance?

Yes, PBPK modeling can be used to predict the performance of drugs in humans prior to obtaining any in-vivo clinical data. Prediction of pharmacokinetic (PK) parameters is more complex than purely prediction of fraction absorbed or DCS assessment. It usually involves us building pre-clinical PBPK models first to demonstrate a robust understanding of the mechanistic behavior (dissolution, absorption, distribution, clearance, and excretion) of the candidate drug in vivo. We then build a human PBPK model utilizing the learnings from the pre-clinical models and incorporating human-specific data, such as human clearance prediction. We use this model to predict human PK performance across a dose range and to conduct risk assessments. We usually perform risk assessments around parameters such as particle size, dose or gastric pH, precipitation risk, and food effect. We can use the information from risk assessments to guide further experiments or the formulation strategy as Phase I clinical trials approach. Although other methods for the prediction of performance in humans can be conducted, PBPK modeling, with verification of predictive performance first performed in pre-clinical species, is superior to empirical methods (e.g. allometry) for predicting PK in humans.

What are the key benefits to our customers when we utilize PBPK modeling during the candidate development phase?

The key benefits of utilizing PBPK modeling early are maximum utilization of early-stage pre-clinical information to inform downstream formulation decision-making. This includes informing the formulation strategy, identifying key experiments to be conducted prior to entering the clinic (e.g. assessing precipitation risk), or performing uncertainty analysis on key parameters, such as clearance, to understand how sensitive this parameter is on predicted PK parameters.

Ultimately, by facilitating a much more robust understanding of a molecule’s behavior earlier, M&S allows for more informed decisions to be made, leading to potentially significant time and cost savings along the drug development path.

To find out more about Quotient Sciences’ candidate development services, click here.


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