Development of drugs for brain diseases requires consideration of pharmacokinetic factors beyond what is typical of non-brain diseases due to the challenge of achieving acceptable BBB penetration that often eliminates drug candidates from further development. Moreover, the complexities of brain tumors, notably heterogeneity and variable BBB function, create additional uncertainties as to which preclinical development paradigms will be most informative on the ability of a candidate drug to achieve therapeutic concentrations. We applied a two-tier screening system to the ON123 series that was relatively parsimonious and efficient to identify compounds suitable for brain tumor chemotherapy.
Tier 1 screening incorporated two types of screens that have rather disparate endpoints, a rapid in silico
screen to eliminate compounds with physicochemical properties that do not favor brain uptake, and a medium throughput cytotoxicity assay to determine potential efficacy in a standard glioma cell line. The rule-based in silico
methodology is not uncommon in drug discovery, and here we made use of a general consensus that compounds of molecular weight greater than 450 Da and very low and high octanol/water partition coefficients do not penetrate into the brain (17
). In addition, we utilized a calculated risk criterion that is similar to the well-known Lipinski’s Rule of 5 that is often used as an indicator of oral drug absorption, and further may also indicate brain penetration as CNS active compounds were found to have fewer hydrogen (H)-bond donors and lower polar surface area than compared to non-CNS compounds; criteria used in the ADMET risk parameter (28
). The glioma cell cytotoxicity screen provides the first measure of compound efficacy and could eventually be used to build a pharmacodynamic profile. Some caution is warranted; however, as the results from a single cancer cell line could be misleading in that false negatives are possible in that some compounds may be active in glioma cells with different genetic characteristics. In general, the U87 glioma model is a robust test of drug activity since it lacks the tumor suppressor, PTEN, and is unable to regulate oncogenic PI3K that often leads to drug insensitivity. This seems to be the case with the ON123 series as only 13 of the 56 compounds possessed IC50 values of <10 μM, and on that basis were chosen for tier 2 screening.
The tier 2 screening procedures used three in vitro
ADME assays that culminated in the identification of ON123300 as the lead compound in the series. In vitro
microsomal half-life studies have been used extensively to obtain intrinsic metabolic clearance and elimination half-life data for prediction of in vivo
hepatic clearance (11
). According to the classification of hepatic blood clearance into low, medium, and high extraction groups, the 13 ON123 compounds were well distributed (see Table ) and a favorable in vitro
correlation in mouse clearance was obtained (see Fig. ).
The two remaining tier 2 assays, MDCK-MDR1 permeability and equilibrium dialysis binding, are used to indicate both the rate [permeability] and extent [binding assays] of drug accumulation in brain. The evaluation criteria for MDCK-MDR1 assay vary with differences due to of expression level of P-gp and cell culture conditions, such as the seeding density and postseeding time. In our study, caffeine, methotrexate, and paclitaxel were used as control compounds for CNS-positive and CNS-negative and P-gp substrates, respectively, and found to agree well with results presented in several recent publications that focused on the use of MDCK-MDR1 cells as screening tool (7
). Based on such agreement, we chose the same threshold values for BBB permeation (compounds with Papp
cm/s have high potential to cross the BBB and those with Papp
cm/s low potential). It should be mentioned that compounds with a Papp
(A–B) in the MDCK-MDR1 cells of lower than 1
cm/s does not necessarily disqualify a drug candidate as being a potential CNS-acting drug. Other parameters, including efflux ratios and unbound fraction, should be taken into consideration to judge the potential brain distribution. In the present study, estimates of Fub
, and Fup
ratio varied by 82-, 31-, and 13-fold, respectively, among the 13 compounds examined (Table ) that highlights that even in the presence of highly variable plasma and brain binding the estimated brain partition coefficient varied much less. In fact, without ON123890 included, the range of predicted brain partition coefficients would have been less than 4-fold (i.e.
, 2.34 to 8.09, Table ).
Implementation of these three in vitro
ADME screens in the selection of new agents for brain tumor chemotherapy greatly enhanced the throughput and the ability to efficiently triage compounds prior to conducting in vivo
pharmacokinetic studies. An important challenge to prevent premature elimination of compounds is to adequately balance the properties derived from each in vitro
assays into a combined selection criteria. As illustrated in Fig. , a number of compounds that had in vitro
human liver microsomal half-life value of >14 min, including ON123230 that possessed the most favorable half-life of 48.9 min, were unable to cross the cell membrane in MDCK-MDR1 assay, which can be explained that when compounds become more polar and less lipophilic, they tend to be more stable in the liver microsomal half-life screen (10
). Incorporation of the parameters from the MDCK-MDR1 and binding assays into a hybrid parameter (i.e.
)) proved to be a reliable indicator of in vivo
brain distribution (see Fig. ) and showed that the compound, ON123300, with the highest hybrid value also had the highest in vivo
brain/plasma partition coefficient. Use of either the MDCK-MDR1 assay or equilibrium binding assays (see Fig. ) alone did not predict brain accumulation to the extent of the hybrid parameter. The hybrid parameter [i.e.
)] improved the ability to predict the brain exposure and is attributed to it accounting for both the rate and extent of brain distribution. In conclusion, an effective screening strategy was developed to select new agents for brain tumor chemotherapy from a series of low molecular weight anticancer agents [ON123x] by the combined use of in silico
, in vitro
cytotoxicity, and in vitro
ADME profiling studies. One compound, ON123300, selected from the approach exhibited favorable cytotoxicity and brain penetration.