Learn more about pKa and LogP determination including:
- Background information
- Assay details and protocol summary
- Data generated for pKa and LogP
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Learn more about the S9 stability assay including:
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Earlier this year, Evotec hosted a complimentary webinar, ‘INDiGO-Select: profiling and selecting your optimal clinical development candidate’.
INDiGO-Select focuses on better understanding (or increasing the knowledge) of the lead molecule chemistry, its physical-chemistry properties and preclinical DMPK and safety profile, helping to minimise the risk of failure during transition into the subsequent development stages. Evotec’s Manager, Integrated Development Programmes, Sabrina Pagliarusco and Senior Scientific Project Leader, Federico Tosini, take the audience on a journey starting with the war on attrition and a deeper dive into the importance of having a well-designed approach to de-risking. A relatively small investment at the candidate selection stage allows early identification of potential developability liabilities and challenges which consequently allow for a quicker reaction, at a lower cost.
Evotec’s approach to integrated solutions in drug development – INDiGO-Select and INDiGO – are then highlighted. The INDiGO-Select package is never the same for the candidate as it depends on the data that is generated during the discovery phase. To identify any gaps and technical risks, the key areas of focus are the chemistry and pharmaceutical properties, DMPK, the PK/PD relationship and preliminary safety assessment. The next stage – INDiGO - then accelerates early drug candidates into the clinic by reducing time from nomination to regulatory submission. The advantage is that this program can be customised based on data generated during the select and be conducted at a unique site while integrated, so all actions can be performed under the same roof.
Two case studies that used the INDiGO-Select package are then highlighted. The first focuses on low bioavailability, where the client – a small Biotech – has a therapeutic target in neurodegenerative diseases. The activities performed and data presented highlight the impact that an INDiGO-Select model can have on the progress of IND-enabling activities. A second example looks at chemistry and preclinical PK variability. For this particular case study, the objective was to increase the knowledge on the candidate profile and its developability, reducing the risks of later failure in the full development phase. In this instance, the compound was characterised further and, thanks to the data generated, some potential issues were identified to be considered and monitored during the customised development phase.
Choosing the INDiGO-Select model has a number of benefits including enhanced quality of selected drug candidates, increased probability of success later in development and an overall reduction of development costs and project timelines.
Discover more about INDiGO-Select by streaming this insightful webinar from our experts now!
STREAM THE WEBINARTags: INDiGO, Blog, ADME/DMPK, IND Enabling Studies/Preclinical Development, INDiGO-Select
Reactive metabolites play a role in drug-induced toxicity. Early stage in vitro screening for electrophilic reactive metabolite formation involves the use of trapping agents such as glutathione (GSH) in the presence of a drug metabolising system.
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Lipophilicity is an essential physicochemical property used to predict compound behaviour with respect to pharmacokinetics, pharmacodynamics and safety.
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In January 2020, the US FDA finalised its 2017 draft regulatory guidance for industry on in vitro DDI studies by publishing the In Vitro Drug Interactions Studies – Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry. This document outlines how experimental in vitro studies should be carried out and provides instruction on how results should be used to determine potential clinical DDI risk.
Functionally, very little has changed between the draft guidance of 2017 and this final version, mainly consisting of clarifications with very few additional requirements. In this blog, we take a closer look at the small differences there are and explain how they impact on data interpretation for in vitro regulatory DDI studies.
In covering the differences from the draft version of the guidance, we will explore metabolism-mediated drug interactions including CYP inhibition, CYP induction and substrate identification (reaction phenotyping) studies, and then discuss transporter inhibition and transporter substrate studies.
Metabolism Mediated Drug Interactions
Initially, the guidance now promotes the investigation of in vitro metabolic studies before conducting first-in-human studies to better inform the necessity and design of clinical PK studies. Further clarifications are focussed on CYP inhibition, induction and enzyme substrate identification.
CYP Inhibition: One of the changes in terms of metabolism mediated drug interactions relates to CYP inhibition where the FDA has indicated that IC50/2 can be used as an estimate of Ki for reversible inhibitors if the probe substrate concentration used is at the Km for the CYP enzyme. This suggests that assessing Ki may no longer be necessary under these conditions – saving both time and cost in DDI assessment. Of further note is that the Ki and KI have been corrected to Ki,u and KI,u to highlight the fact that the unbound values should be used in the calculations.
CYP Induction: The assay design remains the same but the FDA has provided more detail on the data interpretation for CYP induction studies, in particular, for the fold change method. For example, CYP induction is presumed if a concentration-dependent increase in CYP mRNA is observed which is ≥ 2-fold the vehicle control at the expected hepatic concentrations of the drug. The guidance proposes 30-fold of mean unbound maximal steady state plasma concentration at the therapeutic dose as an estimation of the expected hepatic drug concentration. It also recommends, that even if the induction is less than 2-fold, induction potential cannot be ruled out if the increase in CYP mRNA is greater than 20% of the positive control. The alternative methods for calculating CYP induction risk (basic kinetic R3 model and correlation methods) have remained similar to the previous draft guidance.
Enzyme Substrate Identification: In terms of substrate studies, very little has changed, the guidance has extended the panel of possible non-CYP enzymes to consider if CYPs are not found to contribute towards metabolism. These additional enzymes include aldehyde oxidases (AO), carboxylesterases (CES) and sulfotransferases (SULTs) in addition to other non-CYP Phase I and Phase II enzymes.
Transporter Mediated Drug Interactions
Transporter Inhibition: The main change to highlight relates to the basic static equation cut-off for the MATE transporters which has now increased to 0.1 and falls in line with the existing cut-off for the other renal transporters (OATs and OCT2). This amended cut-off is more relaxed than the previous guidance and will reduce the likelihood of investigational drugs being flagged as potential in vivo MATE inhibitors. Another welcome change is the removal of the suggested 30 min pre-incubation time for the duration of the inhibitor pre-incubation step for OATP transporters. This omission recognises research performed by Cyprotex demonstrating that a shorter inhibitor pre incubation time of 15 min is adequate for assessing correct OATP inhibition as no statistically significant difference in IC50 existed following a 15 min or 30 min inhibitor pre-incubation step. Finally, one notable addition to the P-gp and BCRP inhibition guidance is the specific consideration of investigational drugs administered through the parenteral route or of systemically circulating metabolites acting as inhibitors. In these circumstances, a different basic static equation is used to determine DDI risk, namely I1/IC50 (or Ki) ≥ 0.1, where I1 is the total Cmax of the inhibitor drug or metabolite.
Transporter Substrate Identification: Last but not least, both assay design and data interpretation remain relatively unchanged from the draft guidance for transporter substrate studies.
In summary, the majority of the amendments to the draft 2017 guidance focus on the data analysis stage rather than assay design stage. The main changes affect transporter inhibition studies where new cut-offs have been specified for the MATE transporters. One unexpected amendment relates to the use of IC50/2 as an estimate of Ki for reversible CYP inhibitors, potentially reducing the reliance on Ki studies.
With over 20 years’ experience conducting DDI studies, Cyprotex have a team of experts who can guide you through the process and assist in the planning, execution and interpretation of these regulatory studies. Our popular ADME and DDI guides have also been updated to reflect the 2020 guidance and help you further understand why, when, and how to perform these studies.
Contact enquiries@cyprotex.com to discuss your DDI study
updated ADME and DDI guides
Cytochrome P450 (CYP) induction plays an important role in the pharmacokinetics of a drug and can have consequences for drug efficacy through the reduction of plasma half-life, or drug toxicity if elevated levels of toxic metabolites are formed. These effects are commonly observed when one drug has an effect on a co-administered medication – a term known as drug-drug interactions or DDI.
Transcriptional gene activation, mediated by nuclear receptors such as the aryl hydrocarbon receptor (AhR), pregnane X receptor (PXR), and constitutive androstane receptor (CAR), is the most common mechanism of CYP induction. These receptors correlate directly to the expression of CYP1A2 (AhR), CYP2B6 (CAR), and CYP3A4 plus the CYP2C enzymes (PXR). Therefore, receptor activation can be used as an early indicator of potential changes in CYP enzyme expression.
A less common mechanism for CYP induction is through mRNA or enzyme stabilisation. In this case, certain drugs don’t necessarily stimulate CYP enzyme expression, but rather, slow down CYP protein degradation.
In drug discovery, cell-based transactivation assays can be used for identifying CYP induction potential. In this assay, stably or transiently transfected cell lines containing the nuclear receptor to be evaluated and reporter gene vectors are used. Activation of the response elements following receptor heterodimerisation serves as a suitable proxy for CYP induction. Results are typically reported as Emax and EC50, or a concentration-dependent fold activation relative to vehicle control.
For more advanced drug development, such as IND-enabling studies and NDA submission, CYP induction is typically evaluated as part of a more extensive DDI package. At this stage, cryopreserved human hepatocytes are the preferred model with at least three donors assessed to account for inter-individual variability in response. The hepatocytes are typically incubated with the test compound over 48 to 72 hours, and CYP enzyme induction is evaluated by measuring mRNA levels and/or measuring the catalytic activity of an isoform-specific probe substrate. Because mRNA detection isn’t subjected to the masking effects of time dependent inhibition, regulatory authorities such as the US FDA and EMA recommend this method. However, if protein stabilisation is expected, catalytic activity analysis should also be conducted. Once again, results are typically reported as an Emax and EC50, or concentration-dependent fold increase in response relative to the control. In addition, measurement of test compound over several time points on the last day of incubation is encouraged.
The finalisation of the US FDA In Vitro Guidance in January 2020 resulted in some minor changes to data interpretation of results using the fold change method, and were reviewed in our blog, and our updated DDI Regulatory Guide.
View here for more information on CYP induction testing, including protocols and sample data, or download our free ADME guide.
The field of high-throughput ADME (HT-ADME) places a greater demand on the analytical systems supplying end point quantification.
In this review, we focus on:
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Tags: Articles & Whitepapers, ADME/DMPK