The Global Characterisation of a Drug-Dendrimer Conjugate - PEGylated poly-lysine Dendrimer

The recent emergence of drug-dendrimer conjugates within pharmaceutical industry research and development introduces a range of challenges for analytical and measurement science. These molecules are very high molecular weight (100-200kDa) with a significant degree of structural complexity. The characteristics and quality attributes that require understanding and definition, and impact efficacy and safety, are diverse. They relate to the intact conjugate, the various building blocks of these complex systems and the level of the free and bound active pharmaceutical ingredient (API). From an analytical and measurement science perspective, this necessitates the measurement of the molecular weight, impurity characterisation, the quantitation of the number of conjugated versus free API molecules, the determination of the impurity profiles of the building blocks, primary structure and both particle size and morphology. Here we report the first example of a global characterisation of a drug-dendrimer conjugate - PEGylated poly-lysine dendrimer currently under development (AZD0466). The impact of the wide variety of analytical and measurement techniques on the overall understanding of this complex molecular entity is discussed, with the relative capabilities of the various approaches compared. The results of this study are an essential platform for the research and development of the future generations of related dendrimer-based medicines.

Discovery of Clinical Candidate AZD0095, a Selective Inhibitor of Monocarboxylate Transporter 4 (MCT4) for Oncology

Due to increased reliance on glycolysis, which produces lactate, monocarboxylate transporters (MCTs) are often upregulated in cancer. MCT4 is associated with the export of lactic acid from cancer cells under hypoxia, so inhibition of MCT4 may lead to cytotoxic levels of intracellular lactate. In addition, tumor-derived lactate is known to be immunosuppressive, so MCT4 inhibition may be of interest for immuno-oncology. At the outset, no potent and selective MCT4 inhibitors had been reported, but a screen identified a triazolopyrimidine hit, with no close structural analogues. Minor modifications to the triazolopyrimidine were made, alongside design of a constrained linker and broad SAR exploration of the biaryl tail to improve potency, physical properties, PK, and hERG. The resulting clinical candidate 15 (AZD0095) has excellent potency (1.3 nM), MCT1 selectivity (>1000×), secondary pharmacology, clean mechanism of action, suitable properties for oral administration in the clinic, and good preclinical efficacy in combination with cediranib.

Investigating the properties of L-lysine dendrimers through physico-chemical characterisation techniques and atomistic molecular dynamics simulations

Poly(L-lysine) (PLL) dendrimers up to generation 6, both as their ammonium trifluoroacetate salts and their boc-protected intermediates were characterised using multi-detector size exclusion chromatography (MD-SEC) and Taylor dispersion analysis (TDA)...

Exploration of a Nitromethane-Carbonylation Strategy during Route Design of an Atropisomeric KRASG12C Inhibitor

Route design and proof of concept synthesis was conducted on a synthetically challenging atropisomeric KRAS^G12C inhibitor to support clinical API manufacture. Improvements to the synthesis of a chiral piperazine fragment gave reduced step count and streamlined protecting group strategy via the formation and methanol ring opening of an N-carboxy-anhydride (NCA). The complex atropisomeric nitroquinoline was accessed via an early stage salt-resolution followed by a formal two-part nitromethane-carbonylation, avoiding a high temperature Gould-Jacobs cyclization that previously led to atropisomer racemization. The substrate scope of the formal nitromethane-carbonylation strategy was further explored for a range of ortho-substituted bromo/iodo unprotected anilines.

Machine learning meets mechanistic modelling for accurate prediction of experimental activation energies

Accurate prediction of chemical reactions in solution is challenging for current state-of-the-art approaches based on transition state modelling with density functional theory. Models based on machine learning have emerged as a promising alternative to address these problems, but these models currently lack the precision to give crucial information on the magnitude of barrier heights, influence of solvents and catalysts and extent of regio- and chemoselectivity. Here, we construct hybrid models which combine the traditional transition state modelling and machine learning to accurately predict reaction barriers. We train a Gaussian Process Regression model to reproduce high-quality experimental kinetic data for the nucleophilic aromatic substitution reaction and use it to predict barriers with a mean absolute error of 0.77 kcal mol⁻¹ for an external test set. The model was further validated on regio- and chemoselectivity prediction on patent reaction data and achieved a competitive top-1 accuracy of 86%, despite not being trained explicitly for this task. Importantly, the model gives error bars for its predictions that can be used for risk assessment by the end user. Hybrid models emerge as the preferred alternative for accurate reaction prediction in the very common low-data situation where only 100–150 rate constants are available for a reaction class. With recent advances in deep learning for quickly predicting barriers and transition state geometries from density functional theory, we envision that hybrid models will soon become a standard alternative to complement current machine learning approaches based on ground-state physical organic descriptors or structural information such as molecular graphs or fingerprints.

Hybrid reactivity models, combining mechanistic calculations and machine learning with descriptors, are used to predict barriers for nucleophilic aromatic substitution.

Artificial intelligence and automation in computer aided synthesis planning

In this perspective we deal with questions pertaining to the development of synthesis planning technologies over the course of recent years.

Tricyclic Indazoles-A Novel Class of Selective Estrogen Receptor Degrader Antagonists

Herein, we report the identification and synthesis of a series of tricyclic indazoles as a novel class of selective estrogen receptor degrader antagonists. Replacement of a phenol, present in our previously reported tetrahydroisoquinoline scaffold, with an indazole group led to the removal of a reactive metabolite signal in an in vitro glutathione trapping assay. Further optimization, guided by X-ray crystal structures and NMR conformational work, varied the alkyl side chain and pendant aryl group and resulted in compounds with low turnover in human hepatocytes and enhanced chemical stability. Compound 9 was profiled as a representative of the series in terms of pharmacology and demonstrated the desired estrogen receptor α degrader-antagonist profile and demonstrated activity in a xenograft model of breast cancer.

Solubility prediction from first principles: a density of states approach

Solubility is a fundamental property of widespread significance. Its accurate prediction remains a major challenge. We present a novel, efficient approach to solubility prediction for molecules over a range of conditions based on density of states.

AZD9496: An Oral Estrogen Receptor Inhibitor That Blocks the Growth of ER-Positive and ESR1-Mutant Breast Tumors in Preclinical Models

Fulvestrant is an estrogen receptor (ER) antagonist administered to breast cancer patients by monthly intramuscular injection. Given its present limitations of dosing and route of administration, a more flexible orally available compound has been sought to pursue the potential benefits of this drug in patients with advanced metastatic disease. Here we report the identification and characterization of AZD9496, a nonsteroidal small-molecule inhibitor of ERα, which is a potent and selective antagonist and downregulator of ERα in vitro and in vivo in ER-positive models of breast cancer. Significant tumor growth inhibition was observed as low as 0.5 mg/kg dose in the estrogen-dependent MCF-7 xenograft model, where this effect was accompanied by a dose-dependent decrease in PR protein levels, demonstrating potent antagonist activity. Combining AZD9496 with PI3K pathway and CDK4/6 inhibitors led to further growth-inhibitory effects compared with monotherapy alone. Tumor regressions were also seen in a long-term estrogen-deprived breast model, where significant downregulation of ERα protein was observed. AZD9496 bound and downregulated clinically relevant ESR1 mutants in vitro and inhibited tumor growth in an ESR1-mutant patient-derived xenograft model that included a D538G mutation. Collectively, the pharmacologic evidence showed that AZD9496 is an oral, nonsteroidal, selective estrogen receptor antagonist and downregulator in ER(+) breast cells that could provide meaningful benefit to ER(+) breast cancer patients. AZD9496 is currently being evaluated in a phase I clinical trial. Cancer Res; 76(11); 3307-18. ©2016 AACR.

Optimization of a Novel Binding Motif to (E)-3-(3,5-Difluoro-4-((1R,3R)-2-(2-fluoro-2-methylpropyl)-3-methyl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indol-1-yl)phenyl)acrylic Acid (AZD9496), a Potent and Orally Bioavailable Selective Estrogen Receptor Downregulator and Antagonist

The discovery of an orally bioavailable selective estrogen receptor downregulator (SERD) with equivalent potency and preclinical pharmacology to the intramuscular SERD fulvestrant is described. A directed screen identified the 1-aryl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indole motif as a novel, druglike ER ligand. Aided by crystal structures of novel ligands bound to an ER construct, medicinal chemistry iterations led to (E)-3-(3,5-difluoro-4-((1R,3R)-2-(2-fluoro-2-methylpropyl)-3-methyl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indol-1-yl)phenyl)acrylic acid (30b, AZD9496), a clinical candidate with high oral bioavailability across preclinical species that is currently being evaluated in phase I clinical trials for the treatment of advanced estrogen receptor (ER) positive breast cancer.

Abstract DDT01-03: Discovery and pre-clinical pharmacology of AZD9496: An oral, selective estrogen receptor down-regulator (SERD)

With over 70% of breast cancers expressing estrogen receptor alpha protein (ERα), treatment with either anti-hormonal therapies that directly block ERα function (e.g. tamoxifen) or therapies that block the production of estrogen itself (e.g. anastrozole) have proven to be effective treatments for the disease. Following the discovery of the ERα antagonist tamoxifen in the 1960s, identification of the selective estrogen receptor down-regulator (SERD) fulvestrant represented a further step forward in the treatment of advanced ER+ breast cancer, especially in the endocrine resistance setting where ERα appears to be activated by a ligand independent route through other growth factor signaling pathways. In addition, fulvestrant has also shown significant overall survival (OS) results in the FIRST trial comparing 500 mg fulvestrant with anastrozole in first line advanced ER+ve patients where the majority of patients had not received prior endocrine therapy. Given fulvestrant's low bioavailability following intramuscular injection and the levels of ERα protein in clinical samples after treatment, the question remains as to whether an agent that could achieve higher steady state levels of drug more rapidly and drive further decreases in ERα levels would give enhanced clinical benefit. We have identified a novel, potent, non-steroidal SERD that can be administered orally and could yield improved exposure and clinical benefit. This presentation will describe the discovery and pre-clinical pharmacology of AZD9496, a small molecule that can antagonise ERα and induce receptor degradation in breast cancer cell lines at picomolar concentrations. The good oral pharmacokinetic properties of the compound in pre-clinical species led to significant tumor growth inhibition in an endocrine sensitive MCF-7 xenograft model at a dose of 5 mg/kg and >90% reduction in ER-regulated, progesterone receptor (PR) levels. Tumor regressions were seen in a long term estrogen deprived (LTED) in vivo model, representing the aromatase resistant setting, and corresponded with significant reductions in ERα protein levels, >90% at 5 mg/kg dose. AZD9496 also showed antagonist and down-regulation activity against ERα mutant protein both in vitro and in vivo. These findings strongly supported selection of AZD9496 as a clinical candidate for the treatment of ER+ve breast cancer and the drug is now under evaluation in a Phase 1 clinical trial.

Citation Format: Hazel Weir, Mandy Lawson, Rowena Callis, Michael Hulse, Michael Tonge, Gareth Davies, Graeme Walker, Rachel Rowlinson, Jon Curwen, Zena Wilson, Steve Powell, Robert Bradbury, Alfred Rabow, Craig Donald, David Buttar, Richard Norman, Camila de Almeida, Peter Ballard, Gordon Currie, David Andrews, Graham Richmond, Anne Marie Mazzola, Ermira Pazolli, Brendon Ladd, Celina D'Cruz, Chris De Savi. Discovery and pre-clinical pharmacology of AZD9496: An oral, selective estrogen receptor down-regulator (SERD). [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr DDT01-03. doi:10.1158/1538-7445.AM2015-DDT01-03

Abstract 3912: The discovery of AZD4547: An orally bioavailable, potent and selective N-(5-Pyrazolyl)benzamide FGFR1-3 inhibitor

There is increasing evidence that FGFR signaling plays an important role within human cancer, with members of FGFR family acting as driving oncogenes in a significant number of human tumors. Deregulation of FGFR-signaling has been documented within clinical samples of breast multiple myeloma, bladder, endometrial, gastric, squamous NSCLC and prostate cancers. This dysregulation most frequently occurs through gene amplification, or through genetically altered forms of FGFR proteins. This increasing body of evidence implicating FGFR signaling in cancer has provided rationale for the identification and testing of selective inhibitors of FGFR signaling in the clinic. In this presentation, we describe the progress of our FGFR tyrosine kinase inhibitor programme and report the discovery of N-(5-pyrazolyl)benzamide FGFR inhibitors. Early compounds in this series suffered from poor in vivo pharmacokinetic (PK) properties. The key site of metabolism was identified to be at a basic N-methyl group. This group was shown to be located in the solvent channel of the ATP binding site on binding to FGFR1, and modification could be made without causing major changes to intrinsic binding affinity. However, the first compounds identified with low metabolic clearance also showed a significant reduction in oral bioavailability, due to apparent low permeability and increased efflux potential. The characterization of these PK issues and the discovery of compounds which overcame them, through modulation of pKa, lipophilicity and masking of the polar groups, will be described. Leading compounds showed significant anti-tumor activity in xenograft tumors grown in mice. Detailed characterization of these compounds led to the identification of AZD4547, a potent and selective FGFR tyrosine kinase inhibitor currently in Phase I clinical studies.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3912. doi:1538-7445.AM2012-3912

Abstract 4478: Discovery of AZD5363, an orally bioavailable, potent ATP-competitive inhibitor of AKT kinases

AKT is a key node in the most frequently de-regulated signaling pathway in human cancer and has been shown to mediate resistance to a range of cytotoxic, anti-hormonal and targeted therapies. We decided to explore inhibitors of AKT as potential new anti-cancer therapeutics. Here we disclose for the first time the discovery and structure of AZD5363, an orally bioavailable, potent ATP-competitive inhibitor of AKT. We evaluated a range of chemical starting points arising from our previous collaboration with the Institute of Cancer Research and Astex Therapeutics Ltd. Ultimately AZD5363 was discovered following a long journey that started from a pyrrolopyrimidine series of compounds. Our first challenge was to improve potency and a second challenge was to improve ROCK selectivity. ROCK is an AGC kinase like AKT but is involved in regulation of vascular tone and thus blood pressure. Extensive SAR studies exploring the series revealed that achieving selectivity over ROCK while retaining AKT potency was quite challenging. Eventually we discovered ways which could improve both selectivity and potency. However, these compounds had significant activity against the hERG ion channel which is implicated in the development of Torsades de Pointes and cardiac death. The next phase of work therefore had to focus on reducing hERG activity, while at the same time not adversely impacting either AKT potency or ROCK selectivity. Finally we discovered that introduction of a key substituent group provided a compound that achieved reduced hERG potency and, surprisingly, also achieved a further small improvement in both AKT potency and ROCK selectivity. This compound was AZD5363. A crystal structure of AZD5363 bound to AKT has revealed some of the key interactions that may contribute to its potency. For example, the pyrrolopyrimidine appears to form hydrogen bonds to the hinge region of the kinase. AZD5363 inhibits all known AKT isoforms with a potency of <10 nM and inhibits phosphorylation of the AKT substrate, PRAS40 in BT474c cells with a potency of 0.31 μM. Activity in in vivo pharmacodynamic and xenograft models has also been demonstrated. A synthetic route suitable for scale-up has been developed. In conclusion, AZD5363 is a potent inhibitor of AKT in vitro and in cells. It has good hERG and ROCK selectivity. It has pharmacodynamic and xenograft activity in vivo. AZD5363 has potential in cancer therapy and is currently in phase 1 clinical trials.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4478. doi:10.1158/1538-7445.AM2011-4478

Scaffold Hopping Using Clique Detection Applied to Reduced Graphs

Similarity-based methods for virtual screening are widely used. However, conventional searching using 2D chemical fingerprints or 2D graphs may retrieve only compounds which are structurally very similar to the original target molecule. Of particular current interest then is scaffold hopping, that is, the ability to identify molecules that belong to different chemical series but which could form the same interactions with a receptor. Reduced graphs provide summary representations of chemical structures and, therefore, offer the potential to retrieve compounds that are similar in terms of their gross features rather than at the atom-bond level. Using only a fingerprint representation of such graphs, we have previously shown that actives retrieved were more diverse than those found using Daylight fingerprints. Maximum common substructures give an intuitively reasonable view of the similarity between two molecules. However, their calculation using graph-matching techniques is too time-consuming for use in practical similarity searching in larger data sets. In this work, we exploit the low cardinality of the reduced graph in graph-based similarity searching. We reinterpret the reduced graph as a fully connected graph using the bond-distance information of the original graph. We describe searches, using both the maximum common induced subgraph and maximum common edge subgraph formulations, on the fully connected reduced graphs and compare the results with those obtained using both conventional chemical and reduced graph fingerprints. We show that graph matching using fully connected reduced graphs is an effective retrieval method and that the actives retrieved are likely to be topologically different from those retrieved using conventional 2D methods.