Application of sequential factorial design and orthogonal array composite design (OACD) to study combination of 5 prostate cancer drugs

Selectively cross-linked hydrogel-based cocktail drug delivery micro-chip for colon cancer combinatorial drug screening using AI-CSR platform for precision medicine

Cancer, ranked as the second leading cause of global mortality with a prevalence of 1 in 6 deaths, necessitates innovative approaches for effective treatment. Combinatorial drug therapy for cancer treatment targets several key pathways simultaneously and potentially enhances anti-cancer efficacy without intolerable side effects. However, it demands precise and accurate control of drug-dose combinations and their release. In this study, we demonstrated a selectively cross-linked hydrogel-based platform that can quantify and release drugs simultaneously for in-parallel cocktail drug screening. PDMS was used as the flow channel substrate and the poly (ethylene glycol) diacrylate (PEGDA) hydrogel array was formed by UV exposure using the photomask. Employing our platform, cocktails of anticancer drugs are precisely loaded and simultaneously released in-parallel into HCT-116 colon cancer cells, facilitating combinatorial drug screening. The integration of an artificial intelligence-based complex system response (AI-CSR) platform successfully identifies optimal drug-dose combinations from a pool of ten approved drugs. Notably, our cocktail drug chip demonstrates exceptional efficiency, screening 155 drug-dose combinations within a brief two and a half hours, a marked improvement over traditional methods. Furthermore, the device exhibits low drug consumption, requiring a mere 1 μL per patch of chip. Thus, our developed PDMS drug-loaded hydrogel platform presents a novel and expedited approach to quantifying drug concentrations, promising to be a faster, efficient and more precise approach for conducting cocktail drug screening experiments.

Orthogonal array composite designs for drug combination experiments with applications for tuberculosis

The aim of this article is to provide an overview of the orthogonal array composite design (OACD) methodology, illustrate the various advantages, and provide a real-world application. An OACD combines a two-level factorial design with a three-level orthogonal array and it can be used as an alternative to existing composite designs for building response surface models. We compare the D $$ D $$ -efficiencies of OACDs relative to the commonly used central composite design (CCD) when there are a few missing observations and demonstrate that OACDs are more robust to missing observations for two scenarios. The first scenario assumes one missing observation either from one factorial point or one additional point. The second scenario assumes two missing observations either from two factorial points or from two additional points, or from one factorial point and one additional point. Furthermore, we compare OACDs and CCDs in terms of I $$ I $$ -optimality for precise predictions. Lastly, a real-world application of an OACD for a tuberculosis drug combination study is provided.

Murine pharmacokinetics and antimalarial pharmacodynamics of dihydroartemisinin trimer self-assembled nanoparticles

Currently, conjugation of artemisinin-derived dimers, trimers, and tetramers is a viable strategy for developing new effective antimalarial candidates. Furthermore, nanotechnology is an effective means to achieve intravenous administration of hydrophobic drugs. In this paper, an ester-linked dihydroartemisinin trimer (DHA₃) was synthesized and further prepared as self-assembled nanoparticles (DHA₃NPs) by a one-step nanoprecipitation method. The pharmacokinetics and antimalarial pharmacodynamics of DHA₃NPs were studied in rats and mice infected with Plasmodium yoelii BY265 (PyBY265). DHA₃NPs had a regular spherical shape with a uniform size distribution of 140.27 ± 3.59 nm, entrapment efficiency (EE) of 99.63 ± 0.17%, and drug loading efficiency (DL) of 79.62 ± 0.11%. The in vitro release characterization revealed that DHA₃NPs were easily hydrolysed into DHA in an esterase environment. The pharmacokinetics study demonstrated that the area under the concentration-time curve (AUC_0-t) of DHA in DHA₃NPs group was 2070.52 ± 578.76 h×ng×mL^-1, which was higher than that of DHA and artesunate (AS) control groups (AUC_0-t values of 724.18 ± 94.32 and 448.40 ± 94.45 h×ng×mL^-1, respectively) (P < 0.05). The antimalarial pharmacodynamics in vivo suggested that DHA₃NP_S (ED₉₀ 7.82 ± 1.16 μmol×(kg×day)^-1) had a superior antimalarial effect compared with that of control groups (ED₉₀ values of 14.68 ± 0.98 (DHA) and 14.34 ± 1.96 (AS) μmol×(kg×day)^-1) (P < 0.05). In addition, DHA₃NP_S reduced the recurrence ratio and improved the cure ratio and survival time. In summary, DHA₃NPs exhibited promising pharmacokinetic characteristics and antimalarial pharmacodynamics in vivo.

Au-Hemoglobin Loaded Platelet Alleviating Tumor Hypoxia and Enhancing the Radiotherapy Effect with Low-Dose X-ray

Radiotherapy (RT) is a widely explored clinical modality to combat cancer. However, its therapeutic efficacy is not always satisfied because of the severe hypoxic microenvironment in solid tumors and the high dosage of radiation harmful to the adjacent healthy tissue. Herein, Au nanoparticle-hemoglobin complex nanoparticle loaded platelets (Au-Hb@PLT) were fabricated. These Au-Hb@PLT would be activated by tumor cells, and the formed platelet-derivate particles (PM) could deliver Au nanoparticle-hemoglobin complex deeply into tumor tissue because of their small size and tumor homing ability. Hemoglobin acts as an oxygen carrier to relieve the hypoxia and gold nanoparticles work as radiosensitizers to potentiate the sensitivity of tumor cells to X-ray, thus, enhancing the in vivo therapeutic outcome even under a low-dose RT in tumor bearing mice. The enhanced antitumor effect and survival benefits endowed by the Au-Hb@PLT were confirmed in vitro and in vivo. These results demonstrate that these Au-Hb@PLT can work as an oxygen vehicle, offer a promising approach to mitigate hypoxia and improve RT efficacy with a low RT dosage.

In vivo antimalarial activity and pharmacokinetics of artelinic acid-choline derivative liposomes in rodents

It is urgent to develop new antimalarial drugs with good therapeutic effects to address the emergence of drug resistance. Here, the artelinic acid-choline derivative (AD) was synthesized by dehydration reaction and esterification reaction, aimed to avoid the emergence of drug resistance by synergistic effect of artemisinins and choline derivative, which could compete with choline for rate-limiting enzymes in the phosphatidylcholine (PC) biosynthetic pathway. AD was formulated into liposomes (ADLs) by the thin-film hydration method. Efficacy of ADLs was evaluated by Peters 4-day suppression test. The suppression percentage against Plasmodium yoelii BY265 (PyBY265) in ADLs group was higher than those of positive control groups (dihydroartemisinin liposomes, P < 0.05) and other control groups (P ⩽ 0.05) at the doses of 4.4, 8.8, 17.6 µmol (kg·d)−1, respectively. The negative conversion fraction, recrudescence fraction and survival fraction of ADLs group were superior to other control groups. Pharmacokinetics in rats after intravenous injection suggested that ADLs exhibited higher exposure levels (indexed by area under concentration-time curve) than that of AD solution, artelinic acid liposomes or artelinic acid solution (P < 0.01). Taken together, ADLs exhibited promising antimalarial efficacy and pharmacokinetic characteristics.

Artificial intelligence in nanomedicine

The field of nanomedicine has made substantial strides in the areas of therapeutic and diagnostic development. For example, nanoparticle-modified drug compounds and imaging agents have resulted in markedly enhanced treatment outcomes and contrast efficiency. In recent years, investigational nanomedicine platforms have also been taken into the clinic, with regulatory approval for Abraxane® and other products being awarded. As the nanomedicine field has continued to evolve, multifunctional approaches have been explored to simultaneously integrate therapeutic and diagnostic agents onto a single particle, or deliver multiple nanomedicine-functionalized therapies in unison. Similar to the objectives of conventional combination therapy, these strategies may further improve treatment outcomes through targeted, multi-agent delivery that preserves drug synergy. Also, similar to conventional/unmodified combination therapy, nanomedicine-based drug delivery is often explored at fixed doses. A persistent challenge in all forms of drug administration is that drug synergy is time-dependent, dose-dependent and patient-specific at any given point of treatment. To overcome this challenge, the evolution towards nanomedicine-mediated co-delivery of multiple therapies has made the potential of interfacing artificial intelligence (AI) with nanomedicine to sustain optimization in combinatorial nanotherapy a reality. Specifically, optimizing drug and dose parameters in combinatorial nanomedicine administration is a specific area where AI can actionably realize the full potential of nanomedicine. To this end, this review will examine the role that AI can have in substantially improving nanomedicine-based treatment outcomes, particularly in the context of combination nanotherapy for both N-of-1 and population-optimized treatment.

Phosphodiesterase Type 5 (PDE5) Inhibitors Sensitize Topoisomerase II Inhibitors in Killing Prostate Cancer Through PDE5-Independent Impairment of HR and NHEJ DNA Repair Systems

Human castration-resistant prostate cancer (CRPC) is a significant target of clinical research. The use of DNA-damaging agents has a long history in cancer chemotherapy but is limited by their toxicities. The combination with a safer drug can be a strategy in reducing dosage and toxicity while increasing anticancer activity in CRPC treatment. Phosphodiesterase type 5 (PDE5) inhibitors are used to treat erectile dysfunction through the selective inhibition of PDE5 that is responsible for cGMP degradation in the corpus cavernosum. Several studies have reported that PDE5 inhibitors display protective effect against doxorubicin-induced cardiotoxicity. The combinatory treatment of CRPC with doxorubicin and PDE5 inhibitors has been studied accordingly. The data demonstrated that sildenafil or vardenafil (two structure-related PDE5 inhibitors) but not tadalafil (structure-unrelated to sildenafil) sensitized doxorubicin-induced apoptosis in CRPC cells with deteriorating the down-regulation of anti-apoptotic Bcl-2 family members, including Bcl-xL and Mcl-1, and amplifying caspase activation. Homologous recombination (HR) and non-homologous end joining (NHEJ) DNA repair systems were inhibited in the apoptotic sensitization through detection of nuclear foci formation of Rad51 and DNA end-binding of Ku80. PDE5 knockdown to mimic the exposure to PDE5 inhibitors did not reproduce apoptotic sensitization, suggesting a PDE5-independent mechanism. Not only doxorubicin, sildenafil combined with other inhibitors of topoisomerase II but not topoisomerase I also triggered apoptotic sensitization. In conclusion, the data suggest that sildenafil and vardenafil induce PDE5-independent apoptotic sensitization to doxorubicin (or other topoisomerase II inhibitors) through impairment of both HR and NHEJ repair systems that are evident by a decrease of nuclear Rad51 levels and their foci formation in the nucleus, and an inhibition of Ku80 DNA end-binding capability. The combinatory treatment may enable an important strategy for anti-CRPC development.

Application of Mixture Design Response Surface Methodology for Combination Chemotherapy in PC-3 Human Prostate Cancer Cells

Combining chemotherapeutics to treat malignant tumors has been shown to be effective in preventing drug resistance, tumor recurrence, and reducing tumor size. We modeled combination drug therapy in PC-3 human prostate cancer cells using mixture design response surface methodology (MDRSM), a statistical technique designed to optimize compositions that we applied in a novel manner to design combinations of chemotherapeutics. Conventional chemotherapeutics (mitoxantrone, cabazitaxel, and docetaxel) and natural bioactive compounds (resveratrol, piperlongumine, and flavopiridol) were used in 12 different combinations containing three drugs at varying concentrations. Cell viability and cell cycle data were collected and used to plot response surfaces in MDRSM that identified the most effective concentrations of each drug in combination. MDRSM allows for extrapolation of data from three or more compounds in variable ratio combinations, unlike the Chou-Talalay method. MDRSM combinations were compared with combination index data from the Chou-Talalay method and were found to coincide. We propose MDRSM as an effective tool in devising combination treatments that can improve treatment effectiveness and increase treatment personalization, because MDRSM measures effectiveness rather than synergism, potentiation, or antagonism.

Searching Synergistic Dose Combinations for Anticancer Drugs

Recent development has enabled synergistic drugs in treating a wide range of cancers. Being highly context-dependent, however, identification of successful ones often requires screening of combinational dose on different testing platforms in order to gain the best anticancer effects. To facilitate the development of effective computational models, we reviewed the latest strategy in searching optimal dose combination from three perspectives: (1) mainly experimental-based approach; (2) Computational-guided experimental approach; and (3) mainly computational-based approach. In addition to the introduction of each strategy, critical discussion of their advantages and disadvantages were also included, with a strong focus on the current applications and future improvements.

Orthogonal Array composite design to study and optimize antioxidant combinations in the prevention of UVB-induced HSF damage

Excessive exposure to ultraviolet (UV) B radiation may lead to skin damage, photosensitivity, or even tumorigenesis via induction of oxidative stress. Naturally derived antioxidants could play significant roles in cancer therapy due to their multi-targeted actions and lack of substantial toxicity. Drug combinations target at diverse pathway of cells and make cells export meticulous biological outcomes through the multifaceted signaling network. The UVB protective effects of combinations of naturally derived antioxidants- curcumin, resveratrol, proanthocyanidins, baicalein, and beta-nicotinamide adenine dinucleotide (NADH) were investigated. An oxidative cell damage model was established to study the ultraviolet irradiation system. An orthogonal array composite design (OACD) was employed in the optimization of antioxidants combinations. Combination of resveratrol (0.1μM) and baicalein in medium concentration (0.2μM), with NADH in high concentration (0.8μM) was found to be the most efficacious combination among all the 30 runs performed using OACD. The findings suggested that UVB exposure-inflicted cell apoptosis can be significantly reduced by naturally-derived antioxidant combinations. These results provide an insight into the discovery of synergistic antioxidant combinations in skin cancer, using orthogonal array composite design (OACD). The results also have practical implications in the understanding of drug mechanisms in skin cancer, which can assist clinical practice by recommending better drug combinations.