Introduction

A successful drug must combine both potency and drug-like properties. Traditionally, pharmaceutical companies have focused on activity optimization, based on in vitro and in vivo biological assays. Nowadays, many of the pharmaceutical property assays are implemented early in drug discovery, so that properties can be optimized in parallel with activity (Smith, 2002; Kerns, 2001; Kerns and Di, 2003; Di and Kerns, 2003).

Physicochemical properties of drug candidates play an important role in drug discovery and development. A solid drug has to dissolve and permeate through the gastro-intestinal membrane in order to be absorbed into systemic circulation. Therefore, solubility and permeability are two important factors that affect oral absorption.

Solubility not only affects in vivo oral bioavailability, but also has tremendous impact on in vitro assays. Here is an example from a discovery project: a compound was tested in a biological assay, and was not very potent (IC50 = 10 |M). However, owing to the faith that the chemist has in his compound, it was retested. When the biologist retested this compound, she found it was not soluble, and used special conditions to dissolve the compound. This time, the IC50 was 1 nM. By solublizing the compound, the potency increased 1000 fold!

Solubility also affects property assays. Here is an example from our lab: a compound was tested for CYP450 inhibition. The IC50 for 2D6 inhibition, when first tested, was greater than 10 | M. However, when the compound was retested, it was observed to be insoluble in DMSO stock solution. When it was solublized under special conditions, the IC50 was 0.6 |M. Because of the poor solubility of the compound, the assay initiallyunderestimated the potential toxicity due to drug-drug interaction.

Solubility is a prerequisite for many assays. An insoluble compound will be undetected in many Pharmaceutical Profiling assays, such as PAMPA, PAMPA-BBB or pKa determination. In biological assays, if a compound is insoluble in the assay buffer, the activity of the compound will be underestimated. Active compounds may be unnoticed due to insolubility, because very little material was in the test solution. Only when the compound is completely in solution, does measured activity reflect true activity. Insoluble compounds tend to have erratic assay results, give artificially low potency and have poor oral bioavailability. Insoluble compounds can also be challenging for drug development. The burden can be transferred to the patient. For example, due to low aqueous solubility and poor metabolic stability of Amprenavir, patients have to take eight capsules twice a day. Early solubility information can help discovery teams optimize the compounds and reduce the burden for drug development and patient use.

A drug must cross many biological barriers before it can reach the therapeutic target. The barriers can be gastro-intestinal membrane, blood-brain barrier and other cell membranes. Good permeability is essential for good oral bioavailability. For example, a project team discovered a very potent compound containing two carboxylic acid groups with a Ki of 7 nM. However, the compound had low permeability, with a Pe of 0.1 x 10-6 cm/s in PAMPA. The oral bioavailability of the compound was less than 1%. The compound was later modified through a prodrug approach. The monoester prodrug of the compound was quite permeable, with a Pe of 7.0 x 10-6 cm/s in PAMPA. The oral bioavailability of the compound increased to 18%. Unlike solubility, permeability cannot be improved, in general, through formulation. Though, there are several research groups actively studying enhancement of permeability, enhancers are not commonly used in the industry due to potential toxicity (Ward et al., 2000). Improvement of permeability usually requires structural modification.

These examples indicate the major impact that physiochemical properties have. This chapter discusses key physicochemical properties for drug optimization. For each property, methods used to measure the property, applications of the data, strategies for compound improvement, and structure-property relationship are provided.

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