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Introduction

In addition, pKa data can be used for better understanding the binding mechanisms of therapeutic events and also for the optimisation of chemical reactions. A number of ADME properties such as lipophilicity and solubility pH profiles are derived in combination with aqueous pKa data.

This is not surprising as most of the prediction tools are trained by the similar set of commercial drugs. However, it is a useful tool for screening virtual molecules or in the cases where no experimental alternatives are available. The method is very reliable to determine pKa and can analyse about compounds per day. For low soluble compounds, the method employs co-solvents thereby requiring some experience for data interpretation.

In addition, the current size of the titration device still needs a few mg of sample material. Therefore it has been widely accepted in late discovery and early development. Samples are loaded on one end of CE and the migration, or mobility of the compounds is monitored under electric potential. The mobility is highly dependent on the ionisation process and thus pKa data of NCEs can be assessed accordingly 23,38, This tactic demonstrates potential in dealing with some issues in early discovery such as interference of impurities and where only minimal sample material is available.

However, the inability to handle poorly soluble compounds that are highly populated in early phase becomes the major hurdle for its applications in early discovery. A new approach utilising an HPLC method appears to address the issues raised when measuring pKa for sparingly soluble compounds The method establishes a stable and well-defined pH gradient by rapidly mixing acidic and basic buffers, during which drug candidates, predissolved in organic solvent, are introduced at different pH conditions. The spectral changes associated with the variations in ionisation are monitored using an on-line photo-diode-array UV detector to derive pKa values.

With usage of co-solvent in the media, the assay works effectively with poorly soluble NCEs. The pKa data measured on SGA correlate very well with those from the potentiometric titration method. The method exhibits a number of advantages in measuring pKa in early discovery such as being high throughput, automatic, reproducible and economic. In other words, this approach will not work for small molecules such as peptides or other chromophore-containing NCEs where the ionisation occurs at the molecular moiety that is distant from the UV chromophore.

The method may require expertise and good understanding of the underlying principle for data processing in particular for compounds containing multiple pKa values that are close to each other in pH.

511-0030-00L Drug Metabolism and Pharmacokinetics in Drug Product Development

Nonetheless, this tactic can be nicely combined with the potentiometric approach. LogP and LogD are the logarithms of partition co-efficient and apparent partition co-efficient of drug candidates in a lipophilic phase such as octanol and a hydrophilic phase like water. The data are valuable to predict the ADME properties ranging from solubility, permeability to the understanding of transport mechanism. The conventional approach for LogP and LogD determination, the saturation shake-flask method, is to measure the equilibrium distributions of NCEs in octanol and water, not feasible for early discovery.

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The method is reliable but only feasible for compounds with measurable pKa data. Other tactics available to assess LogP and LogD in early stages include liposome chromatography, immobilised artificial membrane IAM chromatography and CE approaches a good review given by Avdeef The latest development for HT-LogP determination is to utilise technology similar to PAMPA where octanol serves as the immobilised phase in a microtiter filter plate Chemical integrity is valuable for the confirmation of chemical identity, in particular for validated hits derived from high-throughput screening where compounds have been stored in DMSO for a long period of time For freshly synthesised NCEs in the lead optimisation phase, it is also beneficial to verify that their chemical structure is as designed as well as confirming the purity.

Chemical stability in general characterises the ability of an NCE to preserve its chemical and physical characteristics under specific conditions.

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From the drugability point of view, stability for solution and solid phases are both critical to foresee the potential issues of a candidate to become a marketed drug. In early discovery, however, the interest is concentrated in the solution phase as drug candidates in early phase are commonly in amorphous or meta-stable states and will be transferred to the more stable polymorphous forms in the development phase.

It is worthwhile to mention that choosing an adequate analytical approach is pivotal to the quality of the chemical stability assay For example, chemical stability in buffer allows for differentiating the issues of chemical and metabolic stability of NCEs. Metabolic stability or clearance, particularly hepatic, is recognised as one of the main determinants of drug concentration in blood and has been used effectively to predict bioavailability and toxicokinetics A metabolically unstable NCE, albeit orally absorbed, might never reach the required therapeutic concentration.

On the other hand, a certain degree of instability might be desirable for a prodrug where a metabolite is more active than its parent. There are a number of tactics to determine metabolic clearance. Whereas comprehensive in vivo PK studies in man serve as the ideal source for ADME data including metabolism, bioavailability and clearance, such experiments are not available until a relatively late phase in drug discovery and during clinical trials. This means that lead optimisation might go down a blind alley in terms of ADME features and produce expensive drug candidates with severe liabilities and ultimate threat of termination.

Animal models, albeit useful in predicting various aspects of the metabolism and PK issues of NCEs in man, require considerable cost and lack the required throughput necessary in early discovery. Furthermore, they do not always show satisfactory predictivity to human clearance due to the difficulties in deriving proper scaling factors at early stages of drug discovery.

Currently, in vitro approaches that are extensively utilised to monitor the metabolic stability as well as to predict the human clearance of drug candidates include the use of recombinant CYP enzymes, liver microsomes, S9 fraction the g supernatant of a liver homogenate , isolated hepatocytes and liver slices The in vitro data derived also demonstrate a decent correlation with the in vivo hepatic clearance values, which are very useful in estimating bioavailability and systemic clearance.

The in vitro method has the advantage of profiling the metabolism of NCEs in the most relevant species and to predict the human hepatic clearance with relatively high throughput and low sample consumption at the earliest stages of drug discovery. The high quality of the assay also allows for the data to be widely utilised in discovery and development stages, appreciably reducing the requirement of animals and offering both commercial and ethical advantages. An alternative approach is to reduce the time points of the depletion determination eg a single time point at minutes, etc 11, This modification may be sufficient to offer the metabolic stability rank-ordering in early discovery, provided that comprehensive metabolic profiling will follow in late discovery.

Another potential issue of the method involves compounds or their metabolised products that inhibit metabolising enzymes such as CYP enzymes. In these cases, it is advisable to collectively interpret the metabolic data along with drug-drug interaction profiling derived from CYP inhibition assay. For NCEs exhibiting high metabolic clearance, it is worthwhile to follow up the metabolism by fully profiling the metabolites, or called metabolite identification. Under those circumstances, the metabolites could be active or inactive to the therapeutic target, which will affect the total efficacy measured.

It could get even worse when the metabolites are found toxic, or show adverse effects, which will raise other toxic and safety issues. A number of methodologies that are used to profile the metabolite identification were reviewed by Watt et al For instance, a drug candidate that is a potent CYP inhibitor may greatly inhibit the metabolism of a co-administered medication, potentially leading to adverse clinical events.


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Therefore, it is essential to screen compounds in early drug discovery to reveal their major metabolic pathways and to monitor their in vitro inhibition of the major CYP isoforms in order to predict their in vivo effects Hence, the inhibition of the above five major isoforms should be measured in a high throughput and fully automated fashion. Commonly one tends to probe the metabolismrelated drug-drug interactions of drug candidates by monitoring the impact of the test compounds on CYP metabolic activity using a known substrate. This is based on the assumption that whenever DDI occurs, regardless of the mechanism s involved eg competitive, non-competitive or uncompetitive , the compound will interfere with the performance of a co-administered drug that is metabolised by the same enzyme For example, in order to accurately quantify the metabolites, one has to ensure that all DDI-induced changes in the metabolism of the designated substrate are completely captured.


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Analytically it is not trivial as all potential metabolites, instead of just the parental compounds as done in most of ADME assays, will need to be quantified. Therefore, the method is more practical in the late discovery and early development phases. This novel methodology therefore substantially improves the throughput, turn-around time and cost-effectiveness by parallel monitoring via a well platereader.

The fully automated method 64 enables us to reliably measure IC50 in duplicate over a broad concentration range 0. In addition, the NCEs that exhibited DDI issues in the end-point experiments can be automatically cherry- picked for further kinetic studies to monitor the whole inhibitory course and derive insights into the mechanisms. The major concern of the fluorogenic approach is for compounds or their metabolites that are fluorescent at the wavelengths used.

However, fluorogenic control experiments are run for all NCEs to raise the flags for compounds or metabolites with potential fluorescent interference. In the last decade, pharmaceutical profiling has made a great leap forward, not only in building up the foundation of comprehensive ADMET diagnostic tools, but also gradually modernising the drug discovery mindset. Nonetheless, this is just the beginning and many unmet needs remain and current assays need to be improved. First, while the pharmaceutical profiling paradise is still in the build-up phase, it is imperative to carefully and constantly appraise the strategy and technical platforms.

In addition, continuous commitments are essential to the development of novel technologies that are crucial to the implementation of early profiling. The technology innovations should be focused on the improvement of quality such as increasing predictivity of the in silico and in vitro suites to the in vivo-PK results. In spite of the considerable expansions in the number of profiling assays in last decade, we are still required to work with the same amount of sample material provided. In addition, the difficulties of sample logistics in handling so many high-throughput profiling assays should never be underestimated.

Finally, one should concentrate on knowledge management of the large collection of profiling data. This leads to two outcomes:.

The impact of early ADME profiling on drug discovery and development strategy

Eventually the productivity of pharmaceutical industry will unlikely be improved unless the in silico-in vitro correlation ISIVC and in vitro-in vivo correlation IVIVC could be properly established and wisely applied in our own drug discovery and development labs. He has been devoted to the establishment of novel techniques in HT ADME profiling and has successfully built up the physico-chemical profiling programme in Novartis, US. He was a visiting professor at Duke University. Using his previous experience in drug discovery and development he is now leading an effort to implement broad scale, early profiling of NCEs.

References 1 DiMasi, JA. New drug development in the United States from to Clinical Pharmacology Therapeutics 69, The price of innovation: new estimates of drug development costs.

Journal of Health Economics 22, — Surviving the Blockbuster Syndrome. Science , Prospects for productivity. Nature Rev. Cutting the cost of drug development? ADMET — turning chemicals into drugs. Nature Biotech. Drug earnings rise, albeit unevenly. Can the pharmaceutical industry reduce attrition rates?

Drug-like properties and the causes of poor solubility and poor permeability. Drug Discovery Today, 6, Pharmaceutical profiling in drug discovery.

Drug Development Process - TOX, ADME, PK/PD, Clinical POC and Drug Approval

Drug Disc. Today, 8, Drug metabolism and pharmacokinetics in drug discovery.

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The Challenge of quality in candidate optimization. Drug Discovery Tech.


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ADMETox in drug discovery: integration of experimental and computational technologies. Drug Discovery Today, 8, Applications of high-throughput ADME in drug discovery.

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