Breakthrough Clinical Results
BrYet US, Inc. has received approval to initiate a first-in-human Phase 1/2 clinical trial of ML-016 in Australia. The trial will evaluate the safety, tolerability, and pharmacokinetics of ML-016 in patients with advanced cancers involving the lungs and/or liver. ML-016 comprises an amino acid polymer conjugated to doxorubicin, targeting the tumor microenvironment. The trial will be conducted at the University of the Sunshine Coast Clinical Trials, with enrollment expected to begin in early 2026. The study aims to explore preliminary antitumor activity in advanced solid tumors involving the lungs and/or liver.
Key Highlights
- BrYet US, Inc. receives approval for first-in-human clinical study of ML-016 in Australia.
- The Phase 1/2 trial will evaluate ML-016 in advanced cancers with lung and/or liver involvement.
- ML-016 targets the vascular endothelium of blood vessels in the tumor microenvironment.
- Trial enrollment is expected to begin in early 2026.
Incidence and Prevalence
Latest Global Estimates of Cancer Incidence and Prevalence
According to GLOBOCAN 2022 estimates, cancer is a significant global health problem with current global evidence indicating there will be a 47% rise of cancer cases for the period 2020-2040.
Breast cancer was identified as the most diagnosed cancer globally. Cancers of esophagus, pancreas, and liver had the highest mortality-to-prevalence and mortality-to-incidence ratios globally. Males and older populations had the highest mortality ratios across regions.
In 2019, the global cancer burdens of respiratory and digestive tracts were 38,568,363.53 and 66,912,328.72 in DALY, 34.28 and 55.32 in ASIR, and 656.82 and 808.22 in ASDR per 100,000 population.
Substantial disparities in cancer burden were observed among 36 cancer types across 185 countries. Low- and middle-income countries had high mortality-to-prevalence ratio (MPR) and mortality-to-incidence ratio (MIR). Human Development Index (HDI) and Gross National Income (GNI) were positively correlated with cancer incidence and mortality but negatively correlated with MPR/MIR.
Regional variations in cancer prevalence show significant geographical disparities. In the U.S., regional disparities show Kentucky, West Virginia, and Mississippi have the highest prevalence of both cancer incidence and mortality. Hotspot analyses identified high cancer incidence and mortality clusters, particularly in the Midwestern and Southern regions of the United States.
In India, which ranks third in terms of cancer incidence in the South-East Asia region, the five most prevalent cancers affecting both genders collectively account for 44% of cancer burden. Indian females exhibit higher crude incidence (104.5) and crude mortality (64.2) rates compared to males (91.5 and 62.2). Approximately three out of every five individuals succumb to death following a cancer diagnosis in India.
In Belgium, cancer incidence among adolescents and young adults (AYAs) increased by 0.4% annually from 66 to 80 per 100,000 person-years but stabilized after 2015. Belgian mortality decreased by 1% annually, from 10 to 7 per 100,000 person-years (2004-2019) among AYAs.
Rural-urban disparities are evident, with people living in isolated rural areas in Maine having higher odds of being diagnosed with later stage colorectal, lung/bronchus, and prostate cancers compared to urban dwellers. In Brazil, rural workers were more likely to present with lymphohematopoietic cancers compared to other occupations.
Molecular differences in cancer types across populations show variations based on ancestry, with increased African ancestry associated with higher odds of somatic mutations in APC, KRAS, and PIK3CA and lower odds of BRAF mutations, while East Asian ancestry was associated with lower odds of mutations in KRAS.
Study Design Parameters
Cancer Trial Design Parameters and Endpoints
Study Designs
Cancer trials employ diverse methodological approaches including systematic analysis of transcriptomic data sets, systematic reviews of prognostic biomarkers, and advanced deep learning approaches for multimodal analyses. Studies frequently utilize retrospective cohort designs with propensity-score matching to reduce selection bias. Analytical techniques include immunohistochemistry (IHC), single-cell transcriptome analysis, RNA-seq analysis, and single-cell resolution analysis of tumor cells.
Modern trials increasingly incorporate machine learning approaches such as survival tree (ST), random survival forest (RSF), and gradient boosting survival analysis (GBSA). There is a trend toward more specific risk-stratified populations rather than broadly-defined "all-comers," particularly in breast cancer trials.
Endpoints and Outcome Measures
Primary Endpoints
- Overall survival (OS) serves as the most frequent primary endpoint (used in 81% of glioma studies)
- Progression-free survival (PFS) commonly appears as a secondary endpoint
- Treatment-related adverse events function as primary endpoints in some studies
Secondary Endpoints
- Disease-free survival (DFS)
- Distant metastasis-free survival (DMFS)
- Locoregional recurrence-free survival (LRFS)
- Recurrence-free survival (RFS)
- Objective response rate (e.g., 36.3% in a 2024 pancreatic cancer study)
- Disease control rate (e.g., 79.9% in a 2024 pancreatic cancer study)
- Tumor-to-background ratio (TBR) for fluorescence-guided surgery
- Genotype prediction (12.5% of glioma studies)
- Response to immunotherapy (6.2% of glioma studies)
Analytical Methods
Trials employ robust statistical approaches including Kaplan-Meier method for survival curve estimation, log-rank tests for comparing survival differences, and Cox proportional hazards regression for univariate and multivariate analyses. Hazard ratios with 95% confidence intervals quantify treatment effects.
Additional analytical techniques include Gene Set Enrichment Analysis (GSEA), DESeq2 for differential gene expression, ClusterProfiler and CancerHallmarks for functional enrichment, and ESTIMATE and CIBERSORT for tumor microenvironment assessment.
Validation Approaches
Validation strategies encompass independent cohort validation, in vitro validation using cell lines, qRT-PCR validation of signature genes, digital PCR method for quantifying gene signatures, and validation across multiple independent datasets.
Emerging Trends
Patient-reported outcomes (PROs) are increasingly incorporated, particularly in solid tumor trials compared to hematologic malignancies. However, PROs currently have limited influence on oncology drug approvals.
Model performance is evaluated using metrics like Harrell's C-index and Brier score. Response evaluation following neoadjuvant therapy uses both radiological (RECIST) and pathological criteria, with pathological complete response (pCR) serving as an important endpoint in neoadjuvant therapy trials.
Next-generation sequencing (NGS) helps identify genetic biomarkers associated with treatment response, while tumor microenvironment analysis through multiplex immunofluorescence (mIF) is increasingly used in immunotherapy trials.
Insufficient Information on ML-016 and Doxorubicin Trials
After thorough analysis, there is insufficient information available to identify other drugs being trialed for the same indication using the same mechanism of action (MoA) as ML-016 and doxorubicin.
While doxorubicin is known to be part of the ABVD regimen (doxorubicin, bleomycin, vinblastine, and dacarbazine) used in certain treatment protocols, specific details about:
- Other drugs with the same mechanism of action
- Clinical trials targeting the same indications
- Intervention models used in these trials
- The specific mechanism of action of ML-016
- Comparative studies between similar drugs
are not available for comprehensive analysis.
The limited information prevents identification of other drugs being trialed for the same indication using identical mechanisms of action, as well as the intervention models employed in such trials.